INSART AI Workflow and Document Intelligence Accelerator

Move a real operational workflow from manual effort to a working AI-assisted pilot on AWS.

Who this is for This six-week accelerator is designed for operations, product, compliance and technology leaders in fintech, financial services and B2B software. It is best suited to workflows that depend on documents, fragmented information, repeated classification, manual review, exception handling or knowledge-intensive decisions.

Standard accelerator scope

• Complete a focused AI-readiness diagnostic covering business value, data, workflow, risk and delivery feasibility
• Define one priority workflow, primary user group, baseline and measurable success criteria
• Map the happy path, exceptions, human approvals and audit requirements
• Ingest agreed documents or business data and connect one agreed source or target system
• Build a working AI-assisted pilot with traceable outputs and human-in-the-loop controls
• Evaluate quality, latency, cost and operational fit against an agreed test set
• Deliver architecture, security notes, runbook, backlog and production roadmap

How AWS is used The reference architecture uses Amazon Bedrock for foundation-model access; Amazon Bedrock Knowledge Bases for grounded retrieval where required; Amazon Bedrock Guardrails for configured safeguards; and Amazon Bedrock AgentCore Runtime, Gateway, Identity and Observability where an agentic runtime is appropriate. Amazon Textract can extract text, tables and fields from documents. AWS Lambda and AWS Step Functions orchestrate processing and approvals, with Amazon API Gateway, Amazon EventBridge and Amazon SQS supporting integrations and events. Amazon S3 and Amazon DynamoDB or Amazon Aurora store agreed data. AWS Identity and Access Management, AWS Key Management Service and AWS Secrets Manager protect access and secrets, while Amazon CloudWatch and AWS CloudTrail support monitoring and auditability. Final service selection depends on the approved use case, region, data classification and customer architecture.

What happens next The pilot produces evidence for a production decision. Production hardening, broader AI workflow automation, AI-augmented product acceleration, additional integrations and managed product evolution are scoped separately through a customer-specific private offer and statement of work.

AWS service charges incurred in the customer's AWS account are separate from this professional-services engagement and remain the customer's responsibility.