STONLINK OS
Governed AI on Claude via AWS Bedrock

The control layer for enterprise AI.

Documents, knowledge, and workflows become one governed pipeline — retrieval, reasoning, tool use, and human review, fully audited.

ModelONLINE

Claude · Bedrock

streaming · healthy

AWS region

us-east-1

VPC · private link

Retrieval

1,240

chunks · 12 sources

Policy checks

48 passed

0 blocked · tool scopes

Reviewer queue

2 pending

awaiting sign-off

Latency

0.9s

320 tok/s · p95

Audit traceSL-82017live

> source_context_loaded

System data flow · Sources → Context → Claude → Agent → Review → Output

Sources

Connected systems
Contracts / policies
Claims packets
CRM · ERP · tickets

Context Engine

Document AI + RAG
PARSE + CHUNK
ACL-AWARE RETRIEVAL
CITED CONTEXT

Claude Reasoning Core

AWS Bedrock · controlled access
active
REASONINGconfidence 0.93

Grounded answer from 12 retrieved sources

SRC 04SRC 11→ REVIEW

Agent

Tool use + policy
PLAN MULTI-STEP
CHECK TOOL POLICY
CALL CONNECTORS

Human Review

HITL checkpoints
APPROVAL QUEUE
OVERRIDE / SIGN-OFF
FEEDBACK LOOP

Output

Audit ready
STRUCTURED JSON
SYSTEM WRITE-BACK
AUDIT LOG
Scroll to explore the platform
The platform

One governed AI layer for document-heavy enterprise work

Stonlink connects document ingestion, permission-aware retrieval, Claude reasoning, tool-controlled agents, human review, and audit-ready outputs in one enterprise operating layer.

01

Read and structure complex documents

Contracts, policies, claims packets, reports, and due diligence files.

02

Answer from trusted knowledge

Permission-aware RAG with source citations and escalation paths.

03

Execute controlled workflows

Agents plan steps, call tools, and route sensitive actions to reviewers.

04

Record every decision

Structured outputs, audit logs, evaluation sets, and usage analytics.

Modules

Three AI modules on a shared governed foundation

AI Document Intelligence● live
msa-2024.pdf
Extracted fields
Governing lawSingapore
Liability capS$2.0m
Term36 months
Auto-renewalYes
Risk queue
2 high5 review7 ok

AI Document Intelligence

Turn contracts, policies, and diligence packets into structured, reviewable data — with every field traced back to its source clause.

10k+
Pages / hour
98%
Field accuracy
100%
Source-traced

Workflow examples

  • Review an MSA for liability, renewal, and obligation risk.
  • Compare policy versions and extract structured changes.
  • Process diligence documents into issues, entities, and summaries.

How it works

  1. 1Ingest
  2. 2Extract
  3. 3Flag risk
  4. 4Human review
  5. 5Export JSON

Capabilities

  • Long-document summarization
  • Clause and obligation extraction
  • Risk issue detection
  • Multi-document comparison
  • Structured output

Connects with

  • SharePoint
  • S3
  • iManage
  • DocuSign

Runs on Claude via AWS Bedrock inside your cloud, with RBAC, audit logging, and human-in-the-loop review built in.

Book a walkthrough of this module
Architecture

Claude on AWS Bedrock, connected through a governed enterprise AI layer.

A technical control layer for document intelligence, RAG knowledge answers, agent tool use, human review, and audited outputs.

Enterprise Sources

Documents + systems

contracts / claims / CRM / ERP

Context Engine

Parse · chunk · classify

clauses / entities / obligations

Permission-aware RAG

ACL-aware retrieval

source citations / row ACLs

Claude Reasoning Core

AWS Bedrock · controlled access

Grounded reasoning with cited context

SRC 04SRC 11REVIEW
confidence 0.93private deployment

Agent Orchestration

Plan · call · review

tool scopes / connector calls

Human Review

HITL control

approve / edit / reject

Audited Outputs

Structured + logged

JSON / write-back / audit logs

Control planeRBACVPC / private linkSource citationsHITL gatesEvaluation setsAudit trailStructured outputs

This is an implementation pattern, not a fixed deployment requirement — each layer adapts to your cloud, data, and compliance posture.

Control layer

Governance built into every answer and action

Access, grounding, review, and monitoring are core platform capabilities, applied to every retrieval, generation, and system action, not bolted on afterwards.

Access

  • Role-based access
  • Permission-aware retrieval
  • Data boundary controls

Grounding

  • Source citations
  • Document context
  • Answer traceability

Review

  • Human approval
  • Sensitive action checkpoints
  • Edit, approve, reject

Monitoring

  • Audit trails
  • Evaluation sets
  • Usage and quality analytics

Security architecture is adapted to each customer's cloud, compliance, and operating requirements.

Industry workflows

Industry workflows built on the same governed AI layer

Each workflow maps source content to grounded AI processing, human review, structured output, and audit evidence.

WorkflowIntakeAI processingReviewBusiness outputAudit signal

Legal and compliance

contracts / policies

MSA + policy setclause extractionlegal approvalredline summarytrace captured

Insurance and finance

claims / reports

claims packetrisk summaryunderwriter checkcase updateevidence linked

Customer operations

tickets / knowledge

support ticketRAG answerrefund exceptionagent handoffconversation log

Enterprise operations

approvals / CRM / ERP

process requestagent planHITL gateCRM / ERP writeaudit trail

Live trace

workflow.legal.redline → review.approval → output.summary

Governance

ACL passed · citations attached

Review queue

3 items pending

Implementation path

From pilot to production without losing control

  1. 01

    Discover

    Map workflows, document types, systems, and risk thresholds.

  2. 02

    Prototype

    Build a focused AI workflow with representative data and evaluation criteria.

  3. 03

    Integrate

    Connect enterprise systems, permissions, review queues, and analytics.

  4. 04

    Operate

    Monitor quality, usage, exceptions, and business impact.

Get started

Build your first governed AI workflow with Stonlink.

Start with one high-value workflow. Stonlink helps map the process, evaluate AI quality, integrate the required systems, and move it into production with governance controls.

  • Map one high-value document, knowledge, or process workflow.
  • Evaluate AI quality against your data with an eval set.
  • Integrate the required systems and governance controls.
  • Move to production with human review and audit trails.

Prefer email? hello@stonlink.com

Book a technical walkthrough

Your details are used only to schedule your walkthrough.