Scope and Readiness
Confirm the workflow, sponsor, representative test set, supported infrastructure, data path, operator, success criteria, scope, and commercial terms.
Focused Private AI Pilot
Evaluate one useful AI workflow before expanding.
Srasta pilots are paid, separately scoped engagements. Start with one workflow, an accountable sponsor, a supported deployment, and evidence both teams agree to review.
Use representative documents, coding tasks, or application inputs. Record the model, runtime, hardware, client, access boundaries, operating responsibilities, and limitations that produced the result.
A useful pilot ends with a decision
Proceed, revise the workflow, extend a specific test, or stop—with the evidence and limitations recorded.
Private inference engine Customer-controlled deployment Admin onboarding and role access Written findings and next-step decision
Who it is for
Teams with a concrete workflow and someone ready to own it.
Best-fit pilots have a business or engineering sponsor, an infrastructure owner, representative tasks, and a decision that the evaluation must support.
Software consultancies Professional-services firms Internal platform teams Engineering organizations Knowledge-intensive operations Teams with customer-controlled infrastructure
Pilot flow
Four phases, one production decision path.
Controlled Deployment
Deploy and verify the agreed Srasta configuration. Record the hardware, model, runtime, client, access settings, versions, and known limitations.
Workflow Validation
Run the agreed examples, including difficult and missing-information cases. Review outputs, sources or tests, denied access, latency, effort, and repeatability.
Executive Readout
Review what passed, what failed, remaining limitations, infrastructure and operating effort, and the evidence behind the next-step decision.
What the pilot proves
Test the complete workflow that your team would operate.
The pilot evaluates the supported configuration and connected client or application used for the chosen task. Planned Membrane and company-agent capabilities are outside the pilot unless separately released and scoped.
- 01Agree on the workflow, examples, configuration, and decision gate.
- 02Verify the supported deployment and the complete data path.
- 03Run representative, difficult, and missing-information cases.
- 04Review source support or code tests with the person judging the work.
- 05Check access behavior, repeatability, latency, and operator effort.
- 06Record findings, limitations, cost assumptions, owners, and the next decision.
Pilot outputs
What both teams should know by the end.
Inference fitCan private models meet the workflow quality, latency, and cost profile?
Data-path fitAre every connection, boundary, and operating responsibility understood?
Workflow valueDoes company-aware AI improve the target workflow?
Access fitDoes the tested configuration allow intended access and deny a defined unauthorized case?
Operational fitCan operators deploy, verify, observe, recover, and upgrade it?
Commercial fitIs there a path to annual platform subscription and expansion?
Request a pilot
Tell us about the workflow and environment.
A founder reviews every request. Describe one workflow, the person who will judge it, your likely deployment target, and the decision you need the evaluation to support.