Provectus

Turns Cowork adoption into measurable efficiency and growth outcomes through leadership activation, practical workflows, and organization-wide enablement.

Helps teams ship software with Claude Code on their own codebase while improving delivery visibility and governing agent use.

Puts a production-tested AI system to work on customer data and systems with measurable outcomes and full code ownership.

Modernizes legacy systems while preserving agreed business behavior, reducing uncertainty, and proving each replacement before cutover.

Helps carriers and MGAs review submissions promptly, focus underwriter judgment on consequential cases, and improve risk selection.

Helps underwriting teams act on live portfolio signals, calibrate appetite from the full submission flow, and inform decisions between review cycles.

Prepares review-ready analysis and client artifacts so asset-servicing analysts can increase throughput while retaining decision authority.

Helps providers reduce avoidable denials and rework by automating routine revenue-cycle checks while keeping people in control of judgment-based decisions.

Connects fragmented patient data into cited evidence so organizations can identify cohorts, understand journeys, and support research and care decisions.

Helps teams create brand-consistent decks and pages with checked claims and human review before sharing.

Catches security issues in AI-written code earlier and enforces tested controls throughout development and before merge.

Helps teams reduce rework and build verified software by giving Claude Code agents shared product context and a structured path from intent to implementation.

Helps teams assess codebase readiness for AI agents, prioritize improvements, and establish delivery baselines to guide progress.

Keeps company records current, triggers workflows from work as it happens, and provides answers linked to their sources.

Helps specialists act on cases with less context rebuilding by preparing source-linked work for review and approval.

Prepares email requests for the right owner, reducing sorting work and helping teams respond with relevant case context.

Services and frameworks that modernize legacy applications, establish AI-assisted development practices, assess engineering readiness, and integrate security and verification into delivery.

Products: Agentic Code Modernization, Agentic SDLC with Claude Code, AI-SDLC Measurement Platform, Security Gates for AI-Written Code, AWOS, the Agentic Workflow Operating System

Automation that combines AI agents, NLP, and intelligent document processing to handle unstructured data, make decisions, and automate complex workflows.

Products: Agentic Email Triage, Agentic Expert Workspace, Asset Flow, Blueprint Activation, Cowork Activation

Capabilities for carriers, MGAs, and reinsurers to process submissions, evaluate risk, support pricing, monitor portfolio exposure, and adjust underwriting appetite while retaining human decision authority.

Products: Submission Flow, Portfolio Lens

Capabilities for identifying, analyzing, and resolving claim denials, managing audits, and supporting coding and risk-adjustment to optimize reimbursement.

Products: Revenue Flow

Capabilities for life sciences organizations, providers, and trial sponsors to integrate patient-level data, assemble cohorts, reconstruct patient journeys, and synthesize traceable evidence for research and clinical decision support.

Products: Evidence Lens

Cowork Activation

A hands-on program that activates Anthropic’s Cowork around business targets. It includes executive labs, administrative setup, function-specific workflows, skills and connectors, team enablement, and measurement against a baseline. Packages range from broad organization-wide activation to focused functional workflows and operating-model rebuilds.

• Measure Results Against Targets
  Connect activation to business targets and assess results against a starting baseline.
• Start With Hands-On Leadership Labs
  Help leaders build with AI on real problems before activation expands.
• Choose A Package That Fits
  Select broad rollout, focused functional activation, or an operating-model rebuild.
• Connect Cowork To Daily Workflows
  Equip teams with skills and system connections relevant to their daily work.
• Configure Cowork For Organization-Wide Use
  Set up access and activation components and provide introductory and hands-on enablement.
• Activate High-Volume Business Functions
  Focus activation on financial efficiency and commercial growth workflows.
• Extend Activation Into Industry Workflows
  Apply skills and connectors to specialized industry processes and systems.
• Enable Champions To Replicate Activation
  Give champions guidance and a runbook to support wider rollout.
• Configure Scope And Request A Quote
  Shape the proposed activation around package, workforce, enablement, and connector needs.

Agentic SDLC with Claude Code

A five-track program co-delivered with Anthropic and AWS that helps teams move from experimentation to production-grade software development. Work takes place on the customer’s real codebase in its environment. The program combines Claude Code enablement, spec-driven workflows, enterprise activation, governance, security, and measurement of adoption, delivery outcomes, ROI, and AI costs.

• Give Agents The Context To Build From
  Align product intent and technical plans before implementation.
• Activate Claude Code On Your Codebase
  Apply the program to real projects and engineering tasks rather than sample exercises.
• Measure Adoption, Outcomes, ROI, And Cost
  Give leaders evidence of transformation progress, delivery outcomes, and AI spending.
• Build Capability Across Five Tracks
  Stack tracks from foundational skills through enterprise activation, governance, and adoption beyond engineering.
• Govern Agent Access And Production Use
  Establish controls for agent permissions, execution, auditability, security, spending, and internal access.
• Connect Agents To Team Tools
  Connect agents to development systems, business tools, and internal services.
• Verify Agent Work Through Automated Checks
  Build evaluation and verification into workflows and track delivery effects.
• Extend Agentic Workflows Across Product Teams
  Help product, analysis, and QA teams participate in the agentic delivery approach.

Blueprint Activation

Deploys and adapts a production-tested AI system for financial services or healthcare. A one-week fixed-fee Sprint measures the current process and assesses fit. An 8–14-week Enable phase deploys and configures the system, and an ongoing Realize phase measures outcomes against the Sprint baseline. Customers receive code, architecture documents, and runbooks at go-live.

• Start With A Proven Baseline
  Build on a production-tested system rather than starting from zero.
• Measure Fit Before Deployment
  Establish a baseline and assess fit before proceeding.
• Align Fees With Measured Outcomes
  Assess deployment and ongoing fees against measured results and the Sprint baseline.
• Adapt The System To Your Business
  Configure the system around customer data, systems, policies, and operating requirements.
• Deploy A Working AI System
  Put a configured system into the customer environment.
• Review And Control Agent Decisions
  Keep people involved in reviewing and controlling agent decisions.
• Trace Agent Actions For Audits
  Provide reviewers with a record of agent actions and provenance.
• Own The Code From Go-Live
  Receive the delivered code and operating documentation at go-live.

Agentic Code Modernization

A Claude-powered modernization service that turns evidence from legacy code and its operators into an agreed specification, target architecture, controlled rebuild, and proof that the replacement works. Agents recover business rules, dependencies, runtime behavior, and undocumented exceptions. Business and engineering owners decide what to keep, change, add, or retire. Rebuilds proceed in reviewed slices with tests, while the legacy system remains untouched until transition is approved. This includes the related Legacy Modernization service approach.

• Recover And Verify Business Rules
  Make business logic and operational knowledge reviewable, including evidence supporting verified rules.
• Approve Scope Before Rebuilding
  Keep business and engineering owners in control of decisions, scope, and acceptance criteria.
• Build To Approved Specs And Tests
  Guide implementation with approved specifications and tests without changing the running legacy system.
• Prove Replacement Behavior Before Cutover
  Compare old and new behavior and record proof before approving transition.
• Assess System Readiness And Risk
  Understand system readiness, connections, size, and risks before deciding what to modernize.
• Map Dependencies And Production Behavior
  Make system structure and runtime behavior reviewable, including components that may not need to be carried forward.
• Design Against Agreed Business Needs
  Translate approved decisions into a reviewable target design and modernization path.
• Redesign Processes Before Systems
  Shape the replacement around current business needs rather than legacy constraints.
• Rebuild And Review One Slice At A Time
  Use a complete pilot to guide subsequent components and preserve reviewable records.
• Harden And Review The Replacement
  Address identified security risks with a reviewable patch.
• Coordinate Agents With Human Review Gates
  Use agents for analysis and implementation while people retain key decisions and approvals.

Submission Flow

A production AI blueprint for carriers and MGAs that supports underwriting from submission intake through triage, risk selection, pricing, binding, and renewal monitoring. Agents extract information, match submissions to appetite, assemble evidence, support pricing, and handle documentation. Routine submissions can clear autonomously, while underwriters retain responsibility for consequential decisions. It connects to existing systems and supports underwriter-curated appetite updates.

• Automate Submission Intake
  Prepare normalized, deduplicated submissions with completeness flags.
• Route Submissions Against Appetite
  Clear routine submissions and direct other cases to the appropriate desk.
• Refresh Underwriting Appetite
  Refine carrier-specific appetite rules from submissions and outcomes with review before deployment.
• Keep Underwriters In Control
  Reserve consequential decisions and exception handling for accountable underwriters.
• Prepare Cited Risk Evidence
  Give underwriters risk profiles with citations to supporting sources.
• Support Evidence-Based Pricing
  Bring comparative exposure context into pricing review.
• Monitor Binding And Renewals
  Support policy issuance and renewal monitoring while informing future appetite decisions.
• Connect Without Replatforming
  Use existing underwriting and policy systems without replacing systems of record.

Portfolio Lens

An underwriting blueprint for carriers, MGAs, and reinsurers. It connects product configuration, underwriting, and portfolio data in a closed loop, monitoring the bound book and learning from accepted and declined submissions. Live appetite signals reach underwriters, product teams, and treaty buyers. Existing systems remain in place, and decision authority stays with responsible people.

• Monitor Portfolio Changes In Near Real Time
  Surface portfolio changes as they emerge rather than waiting for scheduled reviews.
• Calibrate Appetite From Bound And Declined Risks
  Use accepted and declined risks to inform appetite and avoid a bound-book-only view.
• Send Live Appetite Signals To Decisions
  Bring current appetite information to underwriting, product, and treaty decisions.
• Bring Portfolio Signals To Each Decision-Maker
  Present portfolio information suited to each role while keeping decisions with responsible people.
• Align Product Rules With The Live Book
  Help product teams account for current conditions when configuring products and rules.
• Compare The Loop Against Historical Decisions
  Assess proposed signals against the carrier’s own historical data.
• Connect Existing Systems Without Replatforming
  Use existing systems of record while keeping them in place.
• Trace Agent Actions And Decisions
  Keep a record of actions and decision provenance for portfolio signals.

Asset Flow

An agentic layer for asset servicers that prepares document reads, validation, reconciliation, and client-facing artifacts for analyst review. Agents support NAV packs, investor letters, capital call notices, and board decks, while analysts retain decision authority and accountability. It adapts to existing systems without requiring replatforming.

• Prepare Governing-Document Reads
  Reduce mechanical reading while keeping judgment calls with responsible experts.
• Prepare Review-Ready NAV Packs
  Prepare first-pass NAV work for analyst review and sign-off.
• Keep Analysts Accountable For Decisions
  Let agents prepare work while analysts retain responsibility and sign-off.
• Normalize Documents Into Structured Records
  Prepare classified, normalized records from varied documents and formats.
• Verify Allocations And Waterfalls
  Check calculations and allocation logic so analysts can focus on flagged differences.
• Route Exceptions To Analysts
  Direct exceptions to reviewers while allowing prepared work to proceed under selected rules.
• Keep Existing Systems In Place
  Add workflows above systems the team already uses.
• Draft Consistent Investor Letters
  Prepare investor-letter drafts while leaving final approval to analysts.
• Prepare And Cross-Check Capital Calls
  Apply relevant terms and check calculations before analyst review.
• Reconcile Records Across Workflows
  Support consistent information across existing operating systems.
• Assemble Consistent Board Decks
  Prepare board-pack content so leaders can focus on the narrative.
• Support Restructuring And Scenario Analysis
  Extend asset-servicing workflows with restructuring and scenario-analysis skills.

Revenue Flow

An agentic solution for healthcare revenue-cycle operations across eligibility, authorization, documentation, coding, claims, and denials. Six agents share workflow state, clear routine work where appropriate, and surface exceptions for human review. It uses universal, payer-specific, and institution-tuned rules and works with existing systems without replatforming.

• Identify Denial Causes And Support Appeals
  Help teams understand denials and support appeals while reviewing patterns for future checks.
• Adapt Rules To Your Payer And Specialty
  Use payer and specialty rules alongside institution patterns, with review before deployment.
• Automate Routine Work And Escalate Exceptions
  Process routine work autonomously and route judgment-based cases to accountable staff.
• Catch Eligibility Gaps Before Service
  Check eligibility and routing before service to address information gaps early.
• Flag Authorization Risks Earlier
  Surface requirements and potential risks before claim processing.
• Check Claims Before Submission
  Identify issues before claims enter downstream processing.
• Connect Checks Across The Revenue Cycle
  Let information gathered at one stage inform checks at another.
• Support Coding And Charge Capture
  Assist coding and charge-capture workflows while coders retain judgment.
• Connect Existing Revenue-Cycle Systems
  Use existing systems and data sources in the revenue-cycle workflow.
• Support Real-Time Clinical Documentation
  Support documentation during the connected clinical and revenue-cycle workflow.
• Track Revenue-Cycle Performance Against Baselines
  Show revenue-cycle measures and trends, with engagement baselines set before targets are committed.

Evidence Lens

A production AI blueprint for pharma, diagnostics, precision medicine, providers, and trial sponsors. It joins clinical, claims, genomic, multi-omic, and wearable data at patient level, then presents agent-supported evidence through role-specific surfaces. It works above existing data systems and keeps systems of record in place.

• Unify Evidence Across Patient Data
  Bring patient signals together while preserving existing systems of record.
• Answer Questions With Cited Evidence
  Link answers to the underlying records used to produce them.
• Link Records Around Each Patient
  Resolve records across modalities while supporting clinical and commercial use cases.
• Assemble Patients From Cohort Criteria
  Build populations from clinical, molecular, and longitudinal specifications.
• Reconstruct Each Patient Journey
  Bring relevant clinical and molecular evidence into a connected timeline.
• Deploy Within Approved Data Boundaries
  Apply deployment, privacy, and residency controls aligned with each use case.
• Keep Clinical Decisions With Clinicians
  Use agent-generated evidence while preserving clinician decision authority.
• Enrich Profiles With Clinical Features
  Fill profile gaps using clinical notes, laboratory results, and wearable data.
• Retrieve Patient Evidence Semantically
  Make clinical and molecular evidence retrievable for queries and workflows.
• Present Evidence For Each Role
  Shape evidence views around each role and its permitted data access.
• Evaluate Evidence And Monitor For Drift
  Review cohort representation, evaluation results, and drift through an evaluation dashboard.

Brand Voice

A Claude plugin that writes, checks, and builds decks and pages using company brand rules. It transforms topics, notes, transcripts, and existing material into content; creates charts from supplied data; and adds images or image prompts. It checks tone, claims, and layouts, then returns files for human review.

• Draft Content In Your Brand Voice
  Create format-specific content that follows the company’s voice.
• Approve Every File Before It Goes Out
  Keep people responsible for approving content before distribution.
• Apply Your Rules Across Every File
  Establish brand rules once and apply them consistently.
• Build Branded Decks And Pages
  Lay out selected files using company brand rules.
• Check Tone And Keep Your Wording
  Identify voice mismatches and review suggested changes without disregarding supplied source material.
• Check Claims Against Your Sources
  Review claims against sources and request direction when they cannot be confirmed.
• Catch Layout Issues Before Review
  Identify layout problems before returning files for review.
• Turn Data Into Branded Charts
  Convert supplied data into charts that follow company visual rules.
• Use Neutral Defaults When Rules Are Missing
  Avoid applying another company’s brand when rules have not been supplied.
• Add Images Or Image Prompts
  Prepare prompts or include supplied images in content.

Security Gates for AI-Written Code

Adapts existing security workflows for AI-assisted development by placing tested checks where agents read files, change code, add dependencies, or prepare work for merge. The service starts with a read-only baseline and remediation plan, tests controls on one repository, and can then make them mandatory and expand rollout.

• Rotate Exposed Credentials And Prevent Repeat Leaks
  Connect credential findings to owner-led rotation and preventive controls.
• Verify Gates Catch Findings And Fail Safely
  Check that gates behave as intended and do not pass on empty input.
• Require Security Checks On Every Pull Request
  Help prevent security jobs from being skipped before merge.
• Reveal Security Gaps Before Changing The Pipeline
  Identify risks and controls before implementation.
• Check Agent Actions As They Happen
  Record what agent activity ran and what it found.
• Review Dependencies When Manifests Change
  Include security review when package changes occur.
• Block Credential-Shaped Secrets Before Deployment
  Check build outputs before deployment.
• Limit Secrets To The Steps That Need Them
  Reduce the availability of credentials across pipeline workflows.
• Reduce Noise Without Hiding Real Findings
  Address false alarms without suppressing unrelated findings.
• Review Agent Tools And Settings For Changes
  Review changes that shape how development tools and security controls operate.
• Verify Improvements And Extend Controls Across Repositories
  Compare results with baseline and extend tested controls.
• Review Agent Diffs Before Commit
  Require review before commit while noting that the catch rate has not been measured.
• Turn Findings Into Instructions That Prevent Recurrence
  Address both the current finding and conditions that could cause it to recur.

AWOS, the Agentic Workflow Operating System

An open-source framework for Claude Code that guides software development from documented product context and agreed specifications through implementation and verification. It gives agents access to product and architecture knowledge, team conventions, connected sources, specialist agents, and tests. People review and approve key decisions.

• Ground Agents In Product Context
  Give agents a shared record of product purpose, plans, and architecture.
• Agree On Testable Feature Requirements
  Turn intent into testable criteria and surface assumptions before implementation.
• Verify Each Feature Before Completion
  Confirm the result meets agreed criteria before marking work complete.
• Keep People In Control Of Decisions
  Let teams approve key decisions from definition through completed work.
• Approve The Technical Approach
  Review technical assumptions against the existing codebase.
• Delegate Work In Focused Increments
  Give specialist agents manageable tasks with relevant context.
• Equip Agents With Team Practices
  Apply reusable team practices and connect agents to project tools and sources.
• Reuse Project Knowledge Across Work
  Make prior work available to inform later tasks.
• Adapt Workflows To Team Practices
  Configure the process around team documents and conventions.
• Test Prompts And Preserve Customizations
  Check prompts and installations and retain team customizations.

AI-SDLC Measurement Platform

Audits a repository or portfolio to assess readiness for agentic software development. It evaluates codebases across twelve dimensions, returns scores and identified gaps, and provides prioritized remediation recommendations with failed checks and estimated effort. Git history is used to establish delivery measures.

• Measure Twelve Readiness Dimensions
  Use defined checks across engineering practices and requirements introduced by agents.
• Prioritize Actionable Readiness Improvements
  Turn audit findings into an actionable list with priority and effort.
• Assess Readiness Across Codebases
  Identify readiness and improvement needs across one or many repositories.
• Reveal Readiness With A Score
  Provide a measurable starting point for addressing codebase limitations.
• Establish Readiness And Delivery Baselines
  Capture initial readiness and delivery measures for future comparison.
• Track Readiness As Gaps Close
  Measure changes in readiness against defined checks.
• Connect Readiness To Delivery Outcomes
  Follow delivery measures alongside readiness progress.

Barley, Company AI

An internal company AI and reference architecture for building company AI around an organization’s systems, data, and access rules. It reads meetings, tickets, documents, deals, and Slack, updates records from conversations, and answers questions with source links. Its architecture is adapted to each organization rather than delivered as a fixed product.

• Bring Work Context Together
  Draw on relevant information across connected work systems.
• Keep Records Current From Conversations
  Propagate decisions into systems of record instead of relying on manual re-entry.
• Capture Decisions And Owners
  Turn discussions into shareable decisions and follow-up work.
• Verify Answers Against Sources
  Trace answer claims to source records and see information freshness.
• Run Workflows When Events Occur
  Initiate recurring work automatically while retaining approval for system writes.
• Respect Existing Access Rules
  Keep answers aligned with users’ existing information access.
• Find Information Through Meaning And Relationships
  Search company knowledge using both meaning and relationships.
• Resolve The Right Company Or Project
  Disambiguate references before retrieving information.
• Access Barley Across Team Tools
  Use a web interface or supported AI tools to access Barley capabilities.

Agentic Expert Workspace

A role-specific workspace that brings together documents, business records, and tools specialists need to review cases. Built around team processes, it connects existing systems and turns business methods into repeatable agent workflows. Agents gather information, check it against rules, and prepare source-linked work for specialist review and approval.

• Review And Approve Agent Work
  Keep specialists in control before consequential work proceeds.
• Bring Case Context Together
  Provide connected case information without requiring specialists to rebuild context.
• Check Evidence Against Team Rules
  Prepare work against team rules while leaving expert decisions to specialists.
• Trace Findings To Their Sources
  Let specialists inspect evidence before refining or approving work.
• Prepare Assessments And Responses
  Move case work forward with materials specialists can review and refine.
• Turn Team Methods Into Workflows
  Apply team methods consistently across case tasks.
• Connect Existing Systems To Casework
  Fit casework into current platforms and records.
• Keep Case Context In View
  Keep work status and relevant case information visible during review.

Agentic Email Triage

Turns incoming business email into a clear next step. It reads threads and attachments, identifies requests, matches them to cases, applies priority and routing rules, and sends work to the right owner with context. Uncertain matches and decisions requiring judgment go to an authorized expert. The workflow is tailored to existing processes and platforms, with controls for access, approval, audit evidence, and approved processing infrastructure.

• Understand Threads And Attachments
  Review correspondence and attached files together.
• Identify The Request
  Direct messages to appropriate next steps based on their purpose.
• Match Email To The Case
  Connect correspondence to existing work and send uncertain matches for review.
• Route Requests To Owners
  Send prepared requests to the appropriate owner instead of leaving them in an inbox.
• Escalate Uncertain Decisions
  Keep experts involved where confidence is low or judgment is needed.
• Check Updates Before Saving
  Hold incomplete or conflicting changes for review before they reach connected systems.
• Keep Processing In Your Perimeter
  Define the infrastructure boundary for processing and associated components.
• Exclude Personal Mail
  Keep personal messages out of business processing and storage.
• Control Agent Access And Approvals
  Enforce access and approval rules outside the model.
• Apply Priority Rules
  Prioritize requests consistently using configured service and escalation rules.
• Track Requests And Status
  Show ownership, waiting work, and status across correspondence.
• Adjust Rules Without Rebuilding
  Adapt urgency, routing, and approval rules as processes evolve.
• Connect Approved Business Systems
  Fit workflows into existing platforms with access limited to approved records and actions.
• Record Actions With Evidence
  Provide evidence for reviewing actions, rules, approvals, and sources.
• Test Workflows Before Release
  Check workflow behavior against approved examples before release.
• Send Approved Document Requests
  Send permitted document requests while keeping other replies for review.