A 2-week diagnostic for AI work that needs to reach production.
TeqEngine reviews your use case, architecture, data flow, evals, observability, auth boundaries, tool integration, and delivery risk. The output is a decision-grade plan: what to build, what to kill, what to sequence, and what has to be true before production.
When to use it
Use the diagnostic when the opportunity is real, but the path is unclear: the model choice is only one part of the decision, and the hard questions are architecture, data, evals, security, workflow fit, and delivery ownership.
Outputs
- Readiness scorecard, architecture sketch, and 30-day recommendation at the entry scope
- Full executive memo, risk map, eval/harness plan, and 30/60/90-day roadmap for full-scope engagements
- Production risk register with concrete mitigation steps
- Evaluation, observability, auth, and rollback recommendations
- Prioritized roadmap for build, buy, kill, or sequence decisions
- Pilot or implementation scope ready for an SOW
Start broad, or go straight into agentic architecture.
The Diagnostic is packaged in two tracks so the scope matches the decision. The entry track answers whether and how to proceed. The premium track designs the production architecture for teams already building agents, MCP/tool layers, or AI workflow systems. Request a scoping call to determine the right track for your team.
AI Delivery Diagnostic
A focused entry engagement for teams that need a clear build/no-build decision before committing to implementation.
- Readiness scorecard
- Architecture sketch
- 30-day recommendation
- Fit assessment for build, buy, kill, or sequence
Agentic AI / MCP Architecture Diagnostic
A premium architecture track for teams building agents, MCP/tooling layers, copilots, or autonomous workflows.
- MCP/tool boundary design
- Auth, permissioning, and auditability review
- Eval/harness and observability plan
- 30/60/90-day roadmap with a scoped build proposal
What gets reviewed
Use Case Fit
We separate durable AI opportunities from ideas that are better solved with workflow, search, automation, or no build at all.
System Architecture
We review product flow, integration points, data boundaries, model dependencies, and operational failure modes.
Evals and Observability
We define how correctness, cost, latency, drift, and human review should be measured before production traffic arrives.
Security and Governance
We identify privacy, access-control, audit, prompt-injection, and regulated-data concerns early enough to change the design.