{"schemaVersion":1,"profileUrl":"https://nowen.ai/agents/onesix-ai","markdownUrl":"https://nowen.ai/agents/onesix-ai.md","jsonUrl":"https://nowen.ai/agents/onesix-ai.json","name":"OneSix","legalName":"One Six Solutions","website":"https://onesix.ai","location":"Chicago, IL","address":{"city":"Chicago","state":"IL"},"industry":"AI Consulting","deliveryModel":"services","marketCategories":{"primary":{"name":"Data and Analytics Consulting","url":"https://nowen.ai/category/data-and-analytics-consulting"},"others":[{"name":"AI Development Services","url":"https://nowen.ai/category/ai-development-services"}]},"status":{"trust":"unclaimed","text":"Unclaimed: compiled by Nowen from public sources, not reviewed by the company"},"updatedAt":"2026-11-08T15:18:38.389Z","summary":"OneSix helps enterprises design, build, and scale dependable data and AI capabilities through embedded teams and measurable delivery.","description":"OneSix is a data and AI services consultancy that helps enterprises address complex business challenges. It embeds teams within client operations to design strategies, build reliable data and AI systems, and scale capabilities across workstreams. Its work spans data platforms, analytics, artificial intelligence, and governance, with an emphasis on measurable outcomes and leaving clients better equipped to operate and grow.","mission":"To put data and AI to work on hard business problems, building durable systems that leave every client more capable and more profitable.","directory":{"industryName":"AI Consulting","agentCount":16,"indexable":true,"hubUrl":"https://nowen.ai/industry/ai-consulting"},"categoryDirectory":{"name":"Data and Analytics Consulting","agentCount":61,"indexable":true,"url":"https://nowen.ai/category/data-and-analytics-consulting"},"aiReaderFamilies":["OpenAI","Perplexity","Amazon"],"products":[{"name":"Data & AI Strategy","anchor":"product-data-and-ai-strategy","type":"Service","url":"https://www.onesix.ai/services/data-ai-strategy","summary":"Turn data and AI ambition into a prioritized, executable roadmap with clear business value, architecture direction, and ROI targets.","description":"OneSix assesses an organization’s data and AI environment and develops an executable roadmap tied to business outcomes. The 6–10 week engagement covers current-state assessment, use case prioritization, architecture direction, and business case development. Deliverables include a review of platforms, pipelines, capabilities, and existing use cases; a prioritized roadmap; recommendations for architecture and tooling; and ROI targets and funding materials for priority use cases.","pricing":{},"features":[{"name":"Use case prioritization","value":"Focus Investment On High-Value Use Cases","valueDescription":"Give leadership an agreed sequence of use cases based on value, feasibility, and readiness, rather than a wish list of competing initiatives."},{"name":"Architecture direction","value":"Align Architecture With Priority Use Cases","valueDescription":"Make platform and architecture decisions in response to prioritized business needs, while identifying the changes required in the current environment to support delivery."},{"name":"ROI business case","value":"Build A Fundable Case For Investment","valueDescription":"Equip decision-makers with documented value targets and assumptions they can use to evaluate, approve, and fund priority data and AI work."},{"name":"Execution-aligned roadmap","value":"Move Priority Work Toward Delivery","valueDescription":"Give teams a roadmap designed for execution, with ownership, supporting architecture decisions, and ROI targets attached to priority use cases."},{"name":"Current-state assessment","value":"Reveal Constraints And Opportunities","valueDescription":"Gain a clear view of the current environment, its capability and maturity, and the gaps that may affect delivery. This helps leadership understand what to address and where the strongest opportunities lie."}],"marketCategories":[{"name":"Data and Analytics Consulting","url":"https://nowen.ai/category/data-and-analytics-consulting"}]},{"name":"Governance Blueprint","anchor":"product-governance-blueprint","type":"Service","url":"https://www.onesix.ai/services/governance-blueprint","summary":"Creates a practical governance operating model that helps teams use consistent, trustworthy data and govern AI responsibly.","description":"Governance Blueprint is a structured engagement that designs a continuous operating model for trustworthy data and responsible AI. Across core governance, responsible AI, compliance design, and technology direction, OneSix establishes standardized data language and stewardship, AI policies and guardrails, regulatory controls, and vendor-neutral technology recommendations. The 6–8 week engagement produces a designed operating model tailored to the organization’s environment and governance maturity, built to run beyond go-live rather than end as a one-time framework.","pricing":{},"features":[{"name":"Continuous governance operating model","value":"Establish Governance That Continues Beyond Go-Live","valueDescription":"Creates an operating model designed to keep governance functioning after the engagement closes, with a stewardship structure, policy framework, shared language, and continuous operating cadence."},{"name":"Core governance design","value":"Standardize Definitions And Assign Data Stewardship","valueDescription":"Helps teams use consistent data definitions and clarifies who owns, stewards, curates, and certifies each asset. Designed workflows and shared governance practices help bring governance out of departmental silos."},{"name":"Responsible AI framework","value":"Govern AI With Policies And Lifecycle Oversight","valueDescription":"Provides a designed framework for governing how AI is developed and used, with policies, guardrails, oversight, observability, drift monitoring, and fairness testing."},{"name":"Compliance design","value":"Translate Regulations Into Data Controls","valueDescription":"Connects regulatory obligations to the organization’s data and workflows, specifying classification, lineage, policy enforcement, and access controls that support compliance."},{"name":"Governance technology direction","value":"Select Tools That Fit Your Governance Model","valueDescription":"Recommends governance technology after the operating model is designed, so platform choices support the program and suit the organization’s environment, maturity, and scale."}]},{"name":"Data Foundations","anchor":"product-data-foundations","type":"Service","url":"https://www.onesix.ai/services/data-foundations","summary":"Connects and structures business data in a reliable, scalable platform that gives analytics and AI a dependable foundation.","description":"OneSix designs and deploys centralized, production-ready data platforms that connect core business systems and turn raw data into a coherent, reliable layer for analytics and AI. The engagement covers platform architecture, data integration, data modeling, and performance and cost optimization. It can build on an existing platform investment or evaluate options based on data sources, workloads, and team needs. The Snowflake Quickstart Accelerator is delivered as part of a Data Foundations engagement and establishes a production-ready Snowflake environment with configured security, access, cost controls, development conventions, and integration-ready setup. The result is a platform the team can operate and extend, with integration patterns and modeling decisions documented.","pricing":{},"features":[{"name":"Platform architecture","value":"Build A Platform For Production","valueDescription":"Get a centralized platform designed for the workloads it needs to support, with scalable infrastructure and DevOps tooling integrated from go-live."},{"name":"Data integration","value":"Unify Data Across Core Systems","valueDescription":"Bring data from business systems, point solutions, and unstructured sources into one reliable layer using ingestion and orchestration suited to the workload."},{"name":"Rapid environment deployment","value":"Launch A Production-Ready Environment In A Day","valueDescription":"Get a configured Snowflake foundation deployed in a day rather than undertaking a multi-week initial setup."},{"name":"Role-based access and security configuration","value":"Enforce Scoped Access And Built-In Security","valueDescription":"Start with configured identity and network controls, role-based permissions, and a development-scoped setup for Cortex AI."},{"name":"Data modeling","value":"Structure Data For Analytics And AI","valueDescription":"Give downstream analytics and AI a consistent foundation with modeled data, semantic definitions, documented lineage, and metadata."},{"name":"Standardized roles and service accounts","value":"Assign Scoped Roles And Dedicated Service Accounts","valueDescription":"Provide teams and platform tools with defined roles and service accounts, with permissions prepared for common integration patterns."},{"name":"Performance and cost optimization","value":"Control Platform Performance And Costs","valueDescription":"Keep the platform fast as it scales and make usage more predictable through workload tuning, cost monitoring, and capacity planning."},{"name":"Dev, QA, and production data architecture","value":"Structure Environments For Development Through Production","valueDescription":"Establish environment conventions and data architecture that support development, QA where needed, and production."},{"name":"Cost controls","value":"Configure Cost Controls From The Start","valueDescription":"Include cost controls in the initial environment setup rather than leaving them for a later phase."},{"name":"Integration-ready tool access","value":"Connect Common Data And Analytics Tools","valueDescription":"Use prepared service-account access for common integration patterns, including default readiness for Fivetran and compatibility with listed ingestion, transformation, orchestration, and analytics tools."},{"name":"Cortex Code development setup","value":"Enable Cortex Code With Scoped Permissions","valueDescription":"Provide Cortex Code in the development environment using a dedicated role with minimal permissions, with an opt-out where AI is not needed."},{"name":"Environment documentation and handover","value":"Document The Setup For Ongoing Team Use","valueDescription":"Give the team documentation of the environment’s roles, conventions, structure, and configuration decisions so they can maintain and extend what was built."},{"name":"Git integration and dbt scaffold","value":"Include Git And dbt Setup","valueDescription":"Include the Git integration and dbt scaffold identified among the accelerator’s setup components."}]},{"name":"Analytics","anchor":"product-analytics","type":"Service","url":"https://www.onesix.ai/services/analytics","summary":"Give teams trusted, real-time visibility and self-service access to consistent metrics so they can make decisions with confidence.","description":"OneSix designs and deploys an analytics, business intelligence, and conversational layer that gives organizations real-time visibility into current performance and what is coming next. The engagement covers BI platform and semantic-layer design, KPI definitions and ownership, dashboards, automated reporting and alerting, embedded analytics, and natural-language data access. The dashboard and conversational layers use the same KPI framework, with accuracy guardrails and traceable answers. Typical engagements run two to four months and include user enablement to support adoption.","pricing":{},"features":[{"name":"KPI framework","value":"Standardize Metrics Across The Organization","valueDescription":"Establish shared metric definitions, calculations, and ownership to reduce discrepancies and provide a consistent basis for reports, dashboards, and decisions."},{"name":"BI platform and semantic-layer design","value":"Align Analytics With Business Decisions","valueDescription":"Organize analytics around the questions teams need to answer and the workflows where decisions happen, using the existing data layer and tools."},{"name":"Conversational analytics","value":"Ask Data Questions In Plain Language","valueDescription":"Enable users to ask ad hoc questions in natural language and receive responses grounded in governed metrics, with safeguards and traceability to support accuracy and verification."},{"name":"Operational and executive dashboards","value":"Surface Performance In Real Time","valueDescription":"Give operational teams and leaders visibility into the metrics relevant to their workflows, supporting timely decisions based on a shared KPI framework."},{"name":"User enablement and adoption","value":"Support Everyday Analytics Adoption","valueDescription":"Equip users to work with the analytics layer in their day-to-day decisions, supporting adoption beyond initial platform deployment."},{"name":"Automated reporting and alerting","value":"Deliver Timely Reports And Alerts","valueDescription":"Automate reporting and connect alerts to decision-driving metrics so teams can see relevant information and act without depending on manual exports."},{"name":"Embedded analytics","value":"Bring Insights Into Existing Workflows","valueDescription":"Make analytics available within the systems people use to make decisions, rather than requiring them to move between separate tools."}]},{"name":"Artificial Intelligence","anchor":"product-artificial-intelligence","type":"Service","url":"https://www.onesix.ai/services/artificial-intelligence","summary":"Move AI beyond pilots with production systems designed to run reliably, stay accurate, and deliver measurable business value.","description":"OneSix engineers AI systems at scale, including predictive machine learning, computer vision, and LLM and agentic applications. Engagements are scoped around a real business problem, built for the production environment, and instrumented to make ROI visible from launch through retraining. Work can cover use-case development, model training and validation, MLOps and lifecycle management, and application integration. Systems include monitoring and other production capabilities to help maintain performance as data and conditions change.","pricing":{},"features":[{"name":"MLOps and model lifecycle management","value":"Monitor And Retrain Models Over Time","valueDescription":"Monitoring, drift detection, and retraining triggers help teams see performance changes and maintain models as data and conditions evolve."},{"name":"Predictive modeling","value":"Build Models Matched To The Problem","valueDescription":"Model selection and architecture are driven by the problem’s statistical properties, with feature engineering and validation supporting production use."},{"name":"LLM and agent engineering","value":"Deploy LLMs And Agents In Production","valueDescription":"Production-oriented retrieval, orchestration, context, evaluation, and monitoring components support LLM applications and agentic workflows."},{"name":"Computer vision","value":"Apply Vision Models In Operating Workflows","valueDescription":"Models are built for the environment where inference occurs and integrated into workflows where their outputs are used."},{"name":"Application integration","value":"Integrate AI Into Production Workflows","valueDescription":"Integration connects AI outputs to the applications and workflows where they are used, within the production environment."},{"name":"Business use-case development","value":"Scope AI Around Business Problems","valueDescription":"Use-case development ties the technical work to a real business problem and measurable outcomes."},{"name":"Model training and validation","value":"Train And Validate Production Models","valueDescription":"Training and validation prepare models for deployment in their intended production environments."}],"marketCategories":[{"name":"AI Development Services","url":"https://nowen.ai/category/ai-development-services"}]},{"name":"Governance Programs","anchor":"product-governance-programs","type":"Service","url":"https://www.onesix.ai/services/governance-programs","summary":"Keeps governance policies, data quality, access, and lineage operating continuously as data evolves.","description":"OneSix implements governance operating models as running systems, deploying and configuring governance platforms and integrating them with data sources, identity systems, and operational tools. The service automates policy-based access controls, continuously monitors data quality, and provides searchable cataloging, end-to-end lineage, and audit-ready documentation. It can also extend monitoring to AI models through drift detection and observability. Implementations typically take two to four months and are designed to operate after the engagement closes.","pricing":{},"features":[{"name":"Data quality monitoring","value":"Monitor Data Quality Continuously","valueDescription":"Applies quality rules and monitoring to important data domains, with alerts and remediation workflows to address problems before they affect downstream systems."},{"name":"Catalog and lineage","value":"Trace Data Lineage And Maintain Audit Trails","valueDescription":"Makes data assets searchable and their origins and transformations traceable, while continuously producing audit-ready documentation and showing the impact of upstream changes."},{"name":"Access enforcement","value":"Enforce Access Policies And Govern Data Requests","valueDescription":"Applies automated, rules-based access controls according to policy and sensitivity, and supports governed request workflows and self-service discovery of approved data assets."},{"name":"Governance platform deployment","value":"Deploy Governance Platforms Into Existing Environments","valueDescription":"Integrates and configures governance platforms within the organization’s data environment and existing technology stack, aligning the implementation with its operating model and policies."},{"name":"AI model observability","value":"Detect Model Drift And Anomalies","valueDescription":"Monitors AI models for drift and anomalies and provides real-time alerts, extending the governance monitoring discipline beyond data pipelines."}]},{"name":"Operating Partnership","anchor":"product-operating-partnership","type":"Service","url":"https://www.onesix.ai/services/operating-partnership","summary":"Sustain data and AI momentum with an embedded team that continuously advises, identifies opportunities, and delivers work as priorities evolve.","description":"A long-term, embedded relationship with a dedicated team of senior practitioners delivering strategic advisory, an ongoing innovation pipeline, and execution across OneSix’s six service lines. The team carries institutional context across initiatives, supports executive planning and reporting, and scales with changing workloads and priorities. The partnership is designed for organizations running multiple active data and AI workstreams that need continuous delivery rather than disconnected projects.","pricing":{},"features":[{"name":"Embedded execution","value":"Deliver Work With A Dedicated Team","valueDescription":"A team of senior practitioners delivers projects across strategy, governance, data foundations, analytics, AI, and governance programs, with staffing tailored to the workload."},{"name":"Strategic advisory","value":"Align Work With Shifting Priorities","valueDescription":"Executive-level planning and regular roadmap maintenance help keep data and AI work aligned with business goals as priorities change."},{"name":"Delivery continuity","value":"Preserve Context Across Initiatives","valueDescription":"Work can continue with the team’s accumulated knowledge of the organization’s environment, goals, and stakeholders, rather than starting from scratch for each project."},{"name":"Innovation pipeline","value":"Prioritize New Use Cases","valueDescription":"A continuing pipeline of evaluated opportunities helps organizations identify and resource data and AI use cases that fit their strategy and ROI thresholds."},{"name":"Prioritized staffing","value":"Secure Prioritized Team Capacity","valueDescription":"Prioritized staffing and resource allocation help the organization move work forward as needs and priorities change."},{"name":"Preferred pricing","value":"Access Preferred Engagement Pricing","valueDescription":"Preferred pricing is available across partnership engagements, including additional engagements outside the core scope."},{"name":"Platform optimization","value":"Optimize Platforms Over Time","valueDescription":"Ongoing work can include platform optimization as the organization’s data and AI environment evolves."}],"marketCategories":[{"name":"Data and Analytics Consulting","url":"https://nowen.ai/category/data-and-analytics-consulting"}]},{"name":"dbt Cortex Agent","anchor":"product-dbt-cortex-agent","type":"Product","url":"https://www.onesix.ai/accelerators/dbt-cortex-agent","summary":"Manage and deploy Snowflake agents, search services, and MCP servers through existing dbt pipelines with versioning, dependency-aware ordering, and governed access.","description":"The dbt Cortex Agent Accelerator is a proprietary OneSix dbt package that brings Snowflake Cortex Agents, Cortex Search services, and Snowflake-managed MCP servers into dbt workflows as models. Define them in the dbt project and deploy them through its existing CI/CD pipeline, with version control, dependency-aware deployment, and governance. Raw Snowflake specifications pass through verbatim, while dbt ref() dependencies order deployments after the semantic views and search indexes they rely on.","pricing":{},"features":[{"name":"Cortex stack dbt models","value":"Manage Cortex Services In dbt","valueDescription":"Treat agents, search services, and managed MCP servers as dbt models, so teams can define them in their project and run them using dbt."},{"name":"CI/CD pipeline integration","value":"Deploy Through Existing Pipelines","valueDescription":"Use the dbt project’s existing deployment process to ship the Cortex stack alongside code, without introducing separate AI orchestration."},{"name":"Raw Snowflake specification passthrough","value":"Use Snowflake Specs As Written","valueDescription":"Write models using the raw Snowflake agent or MCP server YAML. Verbatim passthrough avoids wrapper limitations and works with new Snowflake features as they ship."},{"name":"Dependency-aware deployment ordering","value":"Deploy Dependencies In Order","valueDescription":"Use dbt dependencies to deploy upstream semantic views and search indexes before the agents and MCP servers that depend on them."},{"name":"Snowflake-managed access governance","value":"Apply Snowflake Access Controls","valueDescription":"Keep agent-related objects under Snowflake role-based access control, with scoped permissions and an audit trail, while data stays in Snowflake."},{"name":"Agent version history","value":"Preserve Agent Change History","valueDescription":"Keep a named history of agent changes on each run, disable versioning for fast development iteration, or use a full refresh to start with a clean history."},{"name":"Idempotent deployments","value":"Rerun Deployments Safely","valueDescription":"Run deployments repeatedly without unsafe duplicate effects. Search indexes are altered in place during steady-state runs, preserving incremental refresh."},{"name":"Shared user feedback capture","value":"Capture Feedback Across Agents","valueDescription":"Collect agent ratings, comments, and conversation context in a shared table using the provided procedure, without building custom logging."}]},{"name":"Agentic AI","anchor":"product-agentic-ai","type":"Service","url":"https://www.onesix.ai/use-case/agentic-ai","summary":"Move AI agents from prototypes into dependable production workflows with governed context, operational controls, and integrations tailored to business processes.","description":"OneSix architects and deploys production agentic systems with deliberate design patterns, a governed context layer, operational integrations, and the infrastructure needed to run reliably at scale. Engagements combine agent development with evaluation, observability, cost discipline, and human escalation controls. A priority agent is validated in production within the first sixty days, establishing reusable runtime, integration patterns, and operational playbooks for subsequent builds.","pricing":{},"features":[{"name":"Production agent deployment","value":"Deploy Agents Into Production","valueDescription":"Validate a priority agent in production within the first sixty days, then use the established runtime and playbooks to support subsequent builds."},{"name":"Governed context layer","value":"Ground Decisions In Governed Context","valueDescription":"Give agents business context and access rules that help make their decisions informed, auditable, and aligned with operational requirements."},{"name":"Agent design pattern selection","value":"Match Architecture To Workloads","valueDescription":"Choose an architecture based on the workload and its failure modes, rather than inheriting an unplanned pattern that may not fit production needs."},{"name":"Workflow and data integrations","value":"Connect Agents To Business Systems","valueDescription":"Integrate agents with data and operational tools so workflows can use relevant information and interact with the systems where work happens."},{"name":"Evaluation and traceability","value":"Evaluate And Trace Agent Behavior","valueDescription":"Score agent performance against relevant data and reconstruct the path behind individual requests to support accountability in production."},{"name":"Human oversight and escalation","value":"Escalate Decisions To People","valueDescription":"Define where people review or take over decisions, including escalation for low-confidence outcomes and checkpoints built into the system architecture."},{"name":"Production monitoring and observability","value":"Monitor Agents In Production","valueDescription":"Observe agent behavior and monitor for drift after deployment, helping teams maintain visibility as systems operate over time."},{"name":"Cost controls","value":"Control Agent Operating Costs","valueDescription":"Apply cost discipline and spend limits to agent workflows to address resource use as systems run at scale."},{"name":"Containerized runtime and CI/CD","value":"Run Agents On Production Infrastructure","valueDescription":"Establish a containerized runtime and CI/CD infrastructure as part of deploying agents for production operation."},{"name":"Industry-specific agent workflows","value":"Adapt Agents To Industry Workflows","valueDescription":"Apply agent workflows to stated industry processes, from proposal and RFP work to student services, clinical operations, and manufacturing tasks."}],"marketCategories":[{"name":"AI Development Services","url":"https://nowen.ai/category/ai-development-services"}]},{"name":"Churn Prediction","anchor":"product-churn-prediction","type":"Service","url":"https://www.onesix.ai/use-case/propensity-risk-modeling#accelerator","summary":"Identify at-risk customers earlier and give teams scores, context, and recommendations to support timely retention interventions.","description":"A Snowflake-native churn prediction system that combines machine learning scoring with Cortex AI. It analyzes structured customer data and unstructured signals from sources such as call notes and emails, weights scores by customer value, and provides context and recommendations. The system includes a conversational interface for querying scores and customer history, alerts when scores change, and periodic retraining using new churn outcomes and account executive feedback.","pricing":{},"features":[{"name":"Multi-source churn scoring","value":"Identify And Prioritize At-Risk Customers","valueDescription":"Combine structured and unstructured customer signals to score churn risk, with scores weighted by customer value to help teams prioritize attention."},{"name":"Churn context and recommendations","value":"Understand Risk And Guide Intervention","valueDescription":"Give teams context about the drivers and triggers behind churn risk, along with recommendations that support timely intervention."},{"name":"Conversational access to churn data","value":"Query Scores And Customer History","valueDescription":"Let users access churn scores, customer history, and aggregate rollups through natural-language queries, with options to extend the interface to Slack, Teams, and existing BI layers."},{"name":"Score-change alerts","value":"Alert Teams When Scores Change","valueDescription":"Surface changes in customer risk scores through an alert pipeline so teams can respond to updated churn signals."},{"name":"Periodic model retraining","value":"Refresh Models With New Outcomes","valueDescription":"Use new churn outcomes and account executive feedback in periodic retraining to keep the model updated as new information becomes available."},{"name":"Reusable source integrations","value":"Connect Common Customer Data Sources","valueDescription":"Use reusable pipeline patterns for common CRM, marketing, support, and commerce data sources."}]},{"name":"Conversational AI","anchor":"product-conversational-ai","type":"Service","url":"https://www.onesix.ai/use-case/conversational-ai","summary":"Gives customers and teams trusted, direct answers from enterprise data, documents, and operational knowledge through natural-language interfaces in tools they already use.","description":"OneSix builds production conversational AI systems that put enterprise data, documents, and operational knowledge behind natural-language interfaces. The systems combine semantic modeling for structured data, retrieval-augmented generation for unstructured content, and integrations with tools users already use. Governance frameworks, verified query patterns, and ambiguity guardrails support accurate, appropriately scoped responses. The Conversational AI Accelerator offers a Snowflake-native query layer using Cortex Analyst, Cortex Search, and Snowflake Intelligence, with role-based access, configurable cost controls, and support for multiple data domains.","pricing":{},"features":[{"name":"Natural-language interface","value":"Ask Questions In Plain Language","valueDescription":"Users can ask questions directly instead of relying on SQL, navigating portals, or waiting for analysts and subject-matter experts."},{"name":"Answer accuracy and ambiguity guardrails","value":"Clarify Ambiguous Questions And Ground Answers","valueDescription":"The system uses governed data definitions and source-grounded retrieval, and can request clarification when a question is ambiguous."},{"name":"Structured data querying","value":"Query Structured Data With Natural Language","valueDescription":"Users can ask questions about business data and metrics without having to know the underlying table schemas or query language."},{"name":"Unstructured content retrieval","value":"Find Answers In Documents And Content","valueDescription":"Users can retrieve information from documents and other unstructured content through the conversational interface."},{"name":"Answer source traceability","value":"Verify Answers Against Their Sources","valueDescription":"Users can inspect the data, model fields, SQL, documents, or passages behind a response to check it against its underlying source."},{"name":"Integration with existing tools","value":"Use Conversational AI In Existing Tools","valueDescription":"Teams can access conversational interfaces in tools and applications they already use, and eligible Tableau and Power BI semantic models can be converted rather than rebuilt from scratch."},{"name":"Governed access and response scope","value":"Respect User Permissions And Data Boundaries","valueDescription":"Responses can be scoped according to user permissions and data boundaries; the Snowflake accelerator inherits configured role-based access."},{"name":"Multi-domain deployment","value":"Expand Across Teams And Data Domains","valueDescription":"Organizations can start with a single team and extend the accelerator to additional semantic models and data domains without rearchitecting."},{"name":"Query cost controls","value":"Control Cortex Credits And Query Costs","valueDescription":"Configurable limits help organizations govern Cortex credit consumption and query costs within the Snowflake accelerator."}]},{"name":"Customer 360","anchor":"product-customer-360","type":"Service","url":"https://www.onesix.ai/use-case/customer-360","summary":"Unify customer data into a trusted profile that helps teams track lifecycle stages, segment audiences, and model customer lifetime value.","description":"OneSix builds production-ready Customer 360 platforms by integrating data from existing systems into a unified customer profile. The solution combines identity resolution, lifecycle tracking, segmentation logic, and customer lifetime value modeling, with an analytics layer and user enablement. A Customer 360 Accelerator offers pre-built data models, integration templates, delivery frameworks, data quality rules, and industry schemas to reduce time to value.","pricing":{},"features":[{"name":"Unified customer profile","value":"Unify Customer Data Across Systems","valueDescription":"Bring customer information together from existing systems into a single profile that teams can use as a trusted basis for their work."},{"name":"Identity resolution","value":"Connect Records To The Same Customer","valueDescription":"Resolve customer identities across source systems so teams can work from unified profiles rather than disconnected records."},{"name":"Lifecycle tracking","value":"Track Customers Across Lifecycle Stages","valueDescription":"Make customer activity and lifecycle stages visible across systems to support lifecycle analysis and management."},{"name":"Customer segmentation","value":"Build More Informed Customer Segments","valueDescription":"Use unified customer data and segmentation logic to support audience building and campaign activation."},{"name":"Customer lifetime value modeling","value":"Model Customer Lifetime Value","valueDescription":"Build a more complete basis for modeling customer lifetime value across customers, cohorts, and channels."},{"name":"Analytics layer deployment and user enablement","value":"Put Customer Insights Into Use","valueDescription":"Deploy an analytics layer and provide user enablement so teams can act on the platform’s unified customer data."},{"name":"Customer 360 Accelerator assets","value":"Accelerate Customer 360 Deployment","valueDescription":"Use pre-built data models, reusable integration patterns, delivery frameworks, and data quality rules to reduce time to value compared with a custom build."},{"name":"Industry-specific schemas","value":"Apply Schemas Built For Your Industry","valueDescription":"Choose purpose-built Customer 360 schema variants for Marketing, Higher Education, or Healthcare & Life Sciences."}]},{"name":"Document Intelligence","anchor":"product-document-intelligence","type":"Service","url":"https://www.onesix.ai/use-case/document-intelligence","summary":"Turn unstructured documents into usable data for analytics, workflows, search, and question answering.","description":"OneSix builds Document Intelligence systems that turn unstructured documents into structured, analytics-ready data. Solutions are designed around specific document types, extraction requirements, and downstream use cases. The Snowflake-native accelerator uses Document AI and Cortex to ingest and extract information, with schemas defined for each document type. Confidence scores and a review application help route uncertain extractions for human review, while governed Snowflake tables make the output available to BI tools and downstream workflows. The extracted corpus can also support semantic search, retrieval-augmented generation, and question answering.","pricing":{},"features":[{"name":"Document ingestion and extraction","value":"Extract Information From Documents","valueDescription":"Process documents that traditional data systems cannot readily query or analyze, including scanned and image-based files. The extraction pipeline is designed to handle varied layouts and content."},{"name":"Confidence scoring and human review","value":"Review Uncertain Extractions","valueDescription":"Route low-confidence fields for human review instead of allowing uncertain results to pass through unchecked. The review app displays source documents alongside extracted data, and reviewer decisions feed back into the pipeline."},{"name":"Schema-driven extraction","value":"Adapt Extraction To Document Types","valueDescription":"Define the information to extract for each document type and update schemas as requirements or document types change, without rebuilding a separate template for every format."},{"name":"Analytics-ready governed output","value":"Prepare Extracted Data For Analytics","valueDescription":"Make structured document data available in governed tables for BI tools, reporting, and downstream analytical workflows."},{"name":"Document search and question answering","value":"Search Documents And Answer Questions","valueDescription":"Use the same parsed corpus for semantic search, retrieval-augmented generation, and question answering over document content."},{"name":"Document-specific solution design","value":"Tailor Extraction To Document Requirements","valueDescription":"Align extraction architecture, schemas, and model configuration with the documents and information requirements relevant to the intended use case."},{"name":"Extraction validation and quality assurance","value":"Validate Extraction Accuracy","valueDescription":"Measure extraction performance against representative documents and relevant use-case metrics, then apply quality assurance and governance practices to monitor accuracy over time."},{"name":"Workflow and system integration","value":"Route Data Into Existing Workflows","valueDescription":"Connect extracted data with the workflows, systems, and people that use it, and support document processing at scale."}]}],"audiences":[],"segments":[],"faq":[],"comparisons":[],"sources":[{"url":"https://onesix.ai","text":"OneSix"},{"url":"https://www.onesix.ai/services/data-ai-strategy","text":"Data & AI Strategy"},{"url":"https://www.onesix.ai/services/governance-blueprint","text":"Governance Blueprint"},{"url":"https://www.onesix.ai/services/data-foundations","text":"Data Foundations"},{"url":"https://www.onesix.ai/services/analytics","text":"Analytics"},{"url":"https://www.onesix.ai/services/artificial-intelligence","text":"Artificial Intelligence"},{"url":"https://www.onesix.ai/services/governance-programs","text":"Governance Programs"},{"url":"https://www.onesix.ai/services/operating-partnership","text":"Operating Partnership"},{"url":"https://www.onesix.ai/accelerators/dbt-cortex-agent","text":"dbt Cortex Agent"},{"url":"https://www.onesix.ai/use-case/agentic-ai","text":"Agentic AI"},{"url":"https://www.onesix.ai/use-case/propensity-risk-modeling#accelerator","text":"Churn Prediction"},{"url":"https://www.onesix.ai/use-case/conversational-ai","text":"Conversational AI"},{"url":"https://www.onesix.ai/use-case/customer-360","text":"Customer 360"},{"url":"https://www.onesix.ai/use-case/document-intelligence","text":"Document Intelligence"}]}