Scope and Readiness
Confirm workflow, data boundaries, model access, infrastructure path, compliance concerns, success metrics, and pilot scope.
Governed AI Pilot
Prove governed AI execution in your own environment.
If you need governance, deployment, and cost-control clarity before a pilot, start with the Private AI Readiness & Cost-Control Diagnostic. The pilot path below is for teams with a sponsor, workflow, and environment ready for scoped engagement.
Srasta pilots are built for regulated-adjacent teams that need private, company-aware AI under enterprise control, with audit evidence and a clear production decision path.
Pilot thesis
Useful AI work against company memory, under enterprise control, with evidence.
Customer-controlled deployment Role-aware model access Governed memory and tools Audit feed and operator visibility
Who it is for
Teams with real governance pressure and a real AI workflow.
Best-fit pilots have a motivated executive sponsor, a concrete workflow, and enough security or compliance pressure that unmanaged AI cannot move into production.
Regional banks Boutique asset managers Mid-cap insurance Specialty pharma Regional health systems Regulated fintech, healthtech, and legaltech
Pilot flow
Four phases, one production decision path.
Controlled Deployment
Deploy Srasta in the customer environment, configure identity-aware access, memory scopes, model routing, and tool policies.
Workflow Validation
Run the selected workflow through governed retrieval, inference, tool, audit, and operator paths.
Executive Readout
Review workflow outcomes, prompt and memory evaluations, policy behavior, audit evidence, operator health, and expansion fit.
What the pilot proves
Governance is evaluated as product behavior, not slideware.
The pilot should show whether Srasta can make AI useful inside company context while keeping model access, memory, tools, and evidence under control.
- 01Admin configures role-based model access.
- 02User asks a company-specific regulated-workflow question.
- 03Srasta retrieves scoped company memory and routes to an approved model.
- 04Tool execution or policy action runs through the governed path.
- 05Prompt, memory, policy, and compliance-rule evaluations are reviewed.
- 06Audit and operator views show what happened and whether the runtime is healthy.
Pilot outputs
What both teams should know by the end.
Governance fitCan the security and compliance story be reasoned about?
Workflow valueDoes company-aware AI improve the target workflow?
Operational fitCan operators deploy, verify, observe, recover, and upgrade it?
Commercial fitIs there a path to annual platform subscription and expansion?