Hexa is an AI-powered platform that automates document-heavy compliance and audit work for enterprise clients. Instead of teams manually cross-checking regulations, reports, and records, Hexa's AI agents read the source documents, apply the rules, and produce structured, traceable output — with every step gated by human approval before it becomes final.
One of its most demanding deployments has been for a banking and corporate client, where Hexa automates a regulatory audit process governed by strict financial-sector compliance rules. The system has to interpret official regulatory documents correctly, work only from verified data, and produce results an auditor can trust and defend — not just plausible-looking AI output.
Who the platform is for
- Project & workflow admins: Configure audit projects, assign documents, and design the AI agent workflow for each use case.
- Compliance & audit teams: Review AI-generated findings, approve or reject results, and track audit progress end-to-end.
- Banking/regulated clients: Rely on the platform to process large volumes of regulatory documents and internal records into structured audit outputs.
What you can do with the platform
- Configure AI agent workflows: Build multi-step, multi-agent workflows visually — no code required — assigning roles, tools, and documents to each step.
- Ground AI in real documents: Ingest regulatory documents and internal records into a retrieval pipeline (RAG) so agents answer from verified sources, not guesses.
- Run structured audits: Generate audit preparation, fieldwork analysis, and final reports that follow a fixed, expected schema — ready for review, not free-form text.
- Gate every AI run with approval: Nothing proceeds to execution or gets published without an explicit human approval step.
- Track everything: Every generated result keeps a trace of which document, rule, or agent step produced it.
How it works for workflow admins
- Create a project and upload the relevant source documents (regulations, reports, records).
- Design the workflow: define agents, assign the model, tools, and documents each agent needs.
- Submit the workflow for publish approval.
- Once approved, trigger a generation run and monitor progress as an async job.
How it works for compliance & audit teams
- Review the AI-generated audit output against source documents and cited rules.
- Approve, request changes, or reject individual findings before anything is finalized.
- Track audit status across preparation, fieldwork, and reporting stages.
- Export or publish the final, approved audit result.
Key benefits
- Regulatory-grade traceability: Every AI output can be traced back to the document and rule it came from — critical for audits that must hold up to scrutiny.
- No hallucinated data: Financial and regulatory figures come only from verified sources; AI never invents numbers or citations.
- Faster audit cycles: Work that used to take teams days of manual cross-referencing is turned into a guided, AI-assisted workflow.
- Configurable, not hardcoded: The same platform adapts to different clients, document sets, and audit rules without rebuilding the system.
- Two-layer approval: Separate gates for publishing a workflow and for approving each AI generation run keep humans in control at every stage.
Featured case: banking & regulatory compliance
For a banking client, Hexa was configured to automate a complex, multi-period regulatory audit process, one of the most demanding use cases the platform has handled:
- Cross-referencing internal data warehouse records against official regulatory documents across multiple reporting periods.
- Applying client-specific business rules and mappings on top of standard regulatory requirements.
- Producing structured, schema-validated audit tables suitable for direct regulator/compliance review.
- Flagging low-confidence or incomplete results explicitly, instead of silently guessing, so nothing unverifiable reaches the final report.
Helpful details
- On-premise ready: Supports local/on-prem LLM deployment for clients with strict data residency and confidentiality requirements.
- Multi-service architecture: Dashboard, AI orchestration, and data layer run as independently deployable services, containerized and orchestrated with Docker/Kubernetes.
- Tool policy control: Every tool an AI agent can use is governed by centralized policy — agent "preference" is never treated as permission.
If you're looking for a way to turn dense, regulation-heavy document work into a controlled, auditable AI workflow, Hexa is built to handle exactly that — from everyday enterprise compliance to strict financial-sector audits.