{"schemaVersion":1,"profileUrl":"https://nowen.ai/agents/observe-ai","markdownUrl":"https://nowen.ai/agents/observe-ai.md","jsonUrl":"https://nowen.ai/agents/observe-ai.json","name":"Observe.AI","website":"https://observe.ai","location":"Redwood City, CA, USA","address":{"city":"Redwood City","state":"CA","country":"USA"},"industry":"Enterprise AI","deliveryModel":"software","marketCategories":{"primary":{"name":"Customer Support Automation Software","url":"https://nowen.ai/category/customer-support-automation-software"},"others":[{"name":"AI Agent Platforms","url":"https://nowen.ai/category/ai-agent-platforms"}]},"status":{"trust":"unclaimed","text":"Unclaimed: compiled by Nowen from public sources, not reviewed by the company"},"updatedAt":"2026-11-06T23:18:43.514Z","summary":"Observe.AI helps organizations improve customer experience and contact center performance with AI-driven conversation support and operational insights.","description":"Observe.AI helps businesses improve customer experience by applying AI across customer conversations, frontline support, and contact center operations. It enables organizations to resolve customer requests, support employees in real time, and analyze interactions to improve service quality and operational performance.","mission":"Building the AI Agent Workforce For Customer Experience","directory":{"industryName":"Enterprise AI","agentCount":75,"indexable":true,"hubUrl":"https://nowen.ai/industry/enterprise-ai"},"categoryDirectory":{"name":"Customer Support Automation Software","agentCount":46,"indexable":true,"url":"https://nowen.ai/category/customer-support-automation-software"},"aiReaderFamilies":["OpenAI","Perplexity","Meta","Amazon"],"boonFrontDoor":{"url":"https://boon.ai/agents/observe-ai","label":"Apply to Observe.AI's partner program through Boon","sub":"Your AI agent writes the proposal: who you are, the fit, and a first step."},"products":[{"name":"Agentic CX Platform","anchor":"product-agentic-cx-platform","type":"Platform","url":"https://www.observe.ai/platform/agent-platform","summary":"Unifies AI agents and interaction intelligence to resolve customer requests, guide frontline teams, and improve CX performance.","description":"Observe.AI’s Agentic CX Platform brings together AI agents for customers, frontline teams, and operations. It supports the full agent lifecycle: building, orchestrating, governing, evaluating, and optimizing agents across voice and digital conversations. Agents connect to enterprise systems to complete workflows, while shared interaction intelligence provides context across the platform. Built-in policies, guardrails, testing, monitoring, and controls support deployment and ongoing improvement. Customer agents resolve requests across voice, chat, web, app, SMS, and social messaging; Companion Agents guide employees before, during, and after interactions; and operations agents analyze performance, provide coaching, and uncover customer insights.","pricing":{},"features":[{"name":"AI agent lifecycle management","value":"Build And Improve AI Agents","valueDescription":"Manage agents across their lifecycle, from building and testing to deployment, monitoring, and optimization."},{"name":"Customer experience agent coordination","value":"Coordinate Agents Across CX","valueDescription":"Connect customer-facing automation, frontline assistance, and operational improvement in a unified system with shared context."},{"name":"Customer request resolution","value":"Resolve Customer Requests Across Channels","valueDescription":"Complete customer service work across voice and digital channels, including actions in connected business systems."},{"name":"System actions and workflow execution","value":"Complete Actions In Connected Systems","valueDescription":"Enable agents to use existing business systems and workflows to take action and complete customer service tasks."},{"name":"Automated operational evaluation and coaching","value":"Evaluate Interactions And Deliver Coaching","valueDescription":"Automate quality evaluation and provide evidence-backed coaching to help teams monitor performance and improve operations."},{"name":"Voice conversation handling","value":"Handle Real-World Calls Naturally","valueDescription":"Support responsive voice conversations that account for caller interruptions, turn-taking, background noise, and specialized vocabulary."},{"name":"Digital channel deployment","value":"Reach Customers Across Digital Channels","valueDescription":"Offer AI support on websites and connect it to messaging channels customers already use."},{"name":"Frontline agent assistance","value":"Guide Frontline Teams In Real Time","valueDescription":"Give employees customer context, knowledge, process guidance, compliance prompts, coaching, and action recommendations throughout interactions."},{"name":"Pre-interaction customer context","value":"Prepare Agents With Customer Context","valueDescription":"Help agents understand who is contacting them, why they may be calling, and what happened previously."},{"name":"In-the-moment process and compliance guidance","value":"Prompt Required Actions During Interactions","valueDescription":"Help agents follow applicable procedures and address compliance requirements while the conversation is in progress."},{"name":"Human handoff and escalation","value":"Transfer Conversations With Full Context","valueDescription":"Route unresolved or higher-risk interactions to people while preserving conversation history and customer context."},{"name":"Knowledge-grounded responses","value":"Answer From Approved Knowledge","valueDescription":"Help agents provide responses based on authorized information rather than unsupported content."},{"name":"Sensitive data handling","value":"Protect Sensitive Interaction Data","valueDescription":"Support secure caller workflows and mask sensitive information in transcripts and actions while enforcing required call steps."},{"name":"Continuous conversation analysis","value":"Surface Emerging Customer Signals","valueDescription":"Monitor conversations for emerging issues and trends that teams can investigate."},{"name":"Natural-language investigation","value":"Investigate Questions In Plain Language","valueDescription":"Explore customer experience data by starting with a question or hypothesis and following signals as an investigation develops."},{"name":"Evidence-backed findings and root-cause analysis","value":"Verify Findings And Explain Root Causes","valueDescription":"Understand the scale and drivers of customer issues through quantified findings grounded in interaction evidence."},{"name":"Agent governance and release controls","value":"Govern Agents With Defined Controls","valueDescription":"Set agent permissions and policies, control releases, and roll back changes to support accountable deployment."},{"name":"Agent simulation and evaluation","value":"Test Agents Before And After Deployment","valueDescription":"Assess agent behavior and outcomes through simulations, regression tests, and scoring to inform release decisions."},{"name":"Shared interaction intelligence","value":"Share Interaction Context Across Agents","valueDescription":"Use interaction signals as shared memory to inform agent actions and support continuity across the customer experience."},{"name":"Interaction data capture and workflow automation","value":"Capture Details And Trigger Workflows","valueDescription":"Reduce manual work by extracting interaction details, preparing form fields, and initiating relevant actions in connected systems."},{"name":"Fallback handling","value":"Recover From Unresolved Interactions","valueDescription":"Provide a safe path when an agent cannot resolve a request or a connected system encounters a problem."},{"name":"Coaching configuration and prioritization","value":"Tailor Coaching To Team Needs","valueDescription":"Focus coaching on specific skills and apply consistent standards and preferred frameworks across teams."},{"name":"Coaching reinforcement and impact tracking","value":"Reinforce And Measure Coaching","valueDescription":"Reinforce relevant practices during conversations and monitor performance changes over time."},{"name":"Action recommendations and cross-functional intelligence","value":"Connect Customer Insights To Business Actions","valueDescription":"Help teams use customer conversation insights to inform cross-functional decisions about products, processes, and business priorities."},{"name":"Live monitoring and operational insights","value":"Monitor Performance And Surface Improvements","valueDescription":"Give teams visibility into live activity and performance trends, with analysis and recommendations to support operational action."},{"name":"Enterprise security and compliance","value":"Operate Within Enterprise Controls","valueDescription":"Support deployment in environments requiring security, privacy, compliance, and visibility into agent performance and actions."},{"name":"Post-interaction documentation","value":"Document Interaction Outcomes","valueDescription":"Create summaries and record dispositions to document completed conversations and next steps."},{"name":"Configurable chat experience","value":"Tailor And Enrich Chat Experiences","valueDescription":"Customize the chat interface and use interactive responses to support customer conversations."}],"marketCategories":[{"name":"Customer Support Automation Software","url":"https://nowen.ai/category/customer-support-automation-software"}]},{"name":"Agent Harness","anchor":"product-agent-harness","type":"Platform","url":"https://www.observe.ai/platform/agent-harness","summary":"Safely test, release, and measure agent changes so teams can improve production AI while maintaining control.","description":"Agent Harness is an AI agent lifecycle management platform that helps operations teams manage agents like critical software. It provides isolated workspaces for safely editing agent logic, version history and change review, simulated conversation testing, release gates, phased traffic rollouts, and one-click rollback. Teams can track KPIs by agent version and link interactions to the version that handled them, making it possible to evaluate changes and trace anomalies. Agent Harness also supports governed knowledge updates, including active syncing from source systems and conflict resolution to keep agents aligned with approved information.","pricing":{},"features":[{"name":"Isolated workspaces and version control","value":"Isolate Changes From Production","valueDescription":"Make and review agent changes in a separate workspace without affecting the version handling live interactions. Full history and side-by-side diffs help teams understand what changed before promoting an update."},{"name":"Phased rollouts and rollback","value":"Roll Out Changes Gradually","valueDescription":"Start with a portion of live traffic, expand when results support it, and use one-click rollback if a change causes problems."},{"name":"Change approvals and release gates","value":"Gate Releases On Reviews And Tests","valueDescription":"Require review and successful evaluation before an agent update reaches customers, helping teams check changes and address regressions before release."},{"name":"Simulated conversation testing","value":"Test Agent Changes Before Release","valueDescription":"Run simulated conversations against a workspace version to evaluate agent behavior before launch, including scenarios that go beyond the happy path."},{"name":"Version-level interaction traceability","value":"Trace Interactions To Agent Versions","valueDescription":"Connect interaction outcomes and anomalies to the precise version and change involved, helping teams understand the impact of releases."},{"name":"Version-level KPI measurement","value":"Compare Performance Across Versions","valueDescription":"Review relevant KPIs side by side across agent versions to assess the impact of an update before committing to full deployment."},{"name":"Governed knowledge syncing","value":"Keep Agent Knowledge Current","valueDescription":"Sync updated policies from source systems and resolve conflicting definitions through governance, helping agents use current, approved information."}]},{"name":"CoBuilder","anchor":"product-cobuilder","type":"Product","url":"https://www.observe.ai/platform/cobuilder","summary":"Helps CX and operations teams turn governed procedures into testable AI agent drafts in plain English, without requiring engineering to author agent logic.","description":"CoBuilder is an AI agent configuration tool that turns policies, procedures, and governed context into complete, working agent drafts. Teams describe what they want an agent to do in plain English; CoBuilder maps the conversation flow, selects actions, and asks clarifying questions when needed. It can use connected systems and available tools, then creates a draft in an isolated Safe Workspace for review and testing. Drafts remain separate from live traffic until they pass the required checks and receive reviewer approval.","pricing":{},"features":[{"name":"SOP and policy ingestion","value":"Turn Existing Procedures Into Agent Inputs","valueDescription":"CoBuilder uses existing policies, procedures, and knowledge sources as the basis for agent configuration, helping teams work from the materials that already define their processes."},{"name":"Plain-English agent authoring","value":"Draft Agents Through Plain-English Collaboration","valueDescription":"CX leads, QA managers, and operations teams can author and refine agents without engineering help or node editors. CoBuilder uses their instructions to draft an agent and asks for clarification rather than guessing when needed."},{"name":"Safe workspace drafts and approval","value":"Review And Test Drafts Before Release","valueDescription":"CoBuilder output remains an isolated workspace draft rather than going live automatically. Teams can review and test it through the Agent Harness lifecycle, and approved changes are required before a version touches real customers."},{"name":"Decision logic mapping","value":"Map Process Logic Automatically","valueDescription":"CoBuilder translates documented procedures into agent logic, including decision branches, fallbacks, and edge cases, reducing the need to construct those flows manually."},{"name":"Connected tool and workflow configuration","value":"Connect Agent Drafts To Governed Tools","valueDescription":"CoBuilder is aware of the connected stack and configures agents to use available systems and tools, avoiding manual tool configuration and integration tickets. Tool calls follow the access controls defined by the team."},{"name":"Compliance checkpoint generation","value":"Build Required Compliance Checks Into Drafts","valueDescription":"CoBuilder incorporates compliance checkpoints from source procedures and QA rubrics into agent drafts, helping teams account for required process steps as they configure agents."}],"marketCategories":[{"name":"AI Agent Platforms","url":"https://nowen.ai/category/ai-agent-platforms"}]},{"name":"Interaction Intelligence","anchor":"product-interaction-intelligence","type":"Platform","url":"https://www.observe.ai/platform/interaction-intelligence","summary":"Turns customer conversations into shared, actionable intelligence to improve quality, understand customer journeys, and guide decisions across teams and AI agents.","description":"Observe.AI Interaction Intelligence analyzes customer conversations across voice and digital channels, scoring quality, extracting structured signals, and stitching interactions into a continuous customer journey. It provides shared, governed intelligence for AI agents, QA teams, and business leaders. The platform supports automated evaluation against quality rubrics, evidence-linked scoring, manual review and calibration, cross-channel case management, and transcription with sensitive-data redaction.","pricing":{},"features":[{"name":"Automated interaction evaluation","value":"Evaluate Every Interaction","valueDescription":"Apply quality criteria consistently across every call and chat, with supporting conversation evidence linked to each score."},{"name":"Cross-channel journey stitching","value":"Unify Customer Journeys","valueDescription":"Give teams and agents a connected view of interactions across channels so they can understand the full issue rather than isolated conversation snippets."},{"name":"Interaction signal extraction","value":"Extract Conversation Signals","valueDescription":"Make customer and operational information in conversations available as structured signals for analysis and agent use."},{"name":"Shared intelligence and journey memory","value":"Share Context Across Agents","valueDescription":"Help connected AI agents ground their answers and actions in shared customer memory, while giving teams a common source of interaction intelligence."},{"name":"Transcription and sensitive-data redaction","value":"Transcribe And Redact Data","valueDescription":"Make conversation content usable as transcripts while masking PII, PCI, and PHI before model processing."},{"name":"Evidence-linked, auditable scoring","value":"Trace Scores To Evidence","valueDescription":"Help teams inspect the conversation moments behind scores and metrics, supporting review and auditability."},{"name":"Manual QA and calibration","value":"Calibrate Human And AI Scores","valueDescription":"Support review of nuanced or high-stakes interactions and help teams align AI scoring with their standards."},{"name":"Interaction pattern and trend discovery","value":"Discover Emerging Patterns","valueDescription":"Surface recurring customer and operational signals across interactions so teams can investigate issues and identify opportunities for improvement."}]},{"name":"Integration Fabric","anchor":"product-integration-fabric","type":"Platform","url":"https://www.observe.ai/platform/integrations","summary":"Connects business systems and runs resilient workflows so agents can use real-time context and complete work across tools.","description":"Integration Fabric connects Observe.AI agents and operations to business systems through more than 250 prebuilt connectors, open APIs, and Model Context Protocol support. Its workflows retrieve live context, run multi-step jobs across connected systems, and continue through slowdowns or outages. Workflows can execute alongside the language model, resume from saved state, and be reused across agents. The platform also supports data synchronization, logging, permissions, auditability, and enterprise data protections.","pricing":{},"features":[{"name":"Durable multi-step workflows","value":"Complete And Resume Multi-Step Jobs","valueDescription":"Run jobs across connected systems from beginning to end, with durable state that allows long-running work to resume and continue after a conversation closes."},{"name":"Prebuilt enterprise connectors","value":"Connect Agents To 250+ Business Systems","valueDescription":"Use prebuilt connectors to link AI agents and operations with systems already used across the business."},{"name":"Real-time context retrieval","value":"Ground Agent Responses In Live Data","valueDescription":"Retrieve relevant customer and account information in real time so agents can use grounded facts when responding."},{"name":"Resilient workflow execution","value":"Recover Workflows From System Failures","valueDescription":"Use retries, timeouts, and fallback paths to handle transient failures and keep multi-step jobs from ending in dead ends."},{"name":"Open APIs and MCP support","value":"Connect Custom Systems With Open APIs And MCP","valueDescription":"Extend connectivity to internal and third-party systems through open APIs and Model Context Protocol support, with governance for those connections."},{"name":"Asynchronous execution alongside the LLM","value":"Keep Conversations Moving During Backend Work","valueDescription":"Run asynchronous and long-running steps alongside the model so conversations do not stall while backend work completes."},{"name":"Data orchestration and synchronization","value":"Enrich And Sync Conversation Data","valueDescription":"Combine conversation data with CRM context and metadata, then synchronize reporting, summaries, and sentiment scores to connected business platforms."},{"name":"Observable and governed workflows","value":"Track And Govern Every Workflow Step","valueDescription":"Use logs, permissions, auditability, and data-access controls to maintain visibility into workflow execution."},{"name":"Enterprise data protection","value":"Protect Data Across Connected Systems","valueDescription":"Apply encryption, PII redaction, and access controls to help protect data as it moves through integrations."}]}],"audiences":[],"segments":[],"faq":[],"comparisons":[],"sources":[{"url":"https://observe.ai","text":"Observe.AI"},{"url":"https://www.observe.ai/platform/agent-platform","text":"Agentic CX Platform"},{"url":"https://www.observe.ai/platform/agent-harness","text":"Agent Harness"},{"url":"https://www.observe.ai/platform/cobuilder","text":"CoBuilder"},{"url":"https://www.observe.ai/platform/interaction-intelligence","text":"Interaction Intelligence"},{"url":"https://www.observe.ai/platform/integrations","text":"Integration Fabric"}]}