Regression suites, red-team libraries, and policy-as-code—shipping models with evidence, not optimism.
Ship prompts and models with tests—safety metrics your risk committee can read
We centralize prompt versions, model endpoints, and evaluation datasets—CI runs faithfulness, toxicity, and jailbreak probes before anything reaches production. Guardrail layers combine regex, classifiers, and LLM judges with configurable escalation to human review. Dashboards track drift when upstream models change—alerts fire when win rates drop on golden sets, not when Twitter notices first.
01 // THE MANDATE
Regression suites, red-team libraries, and policy-as-code—shipping models with evidence, not optimism.
We centralize prompt versions, model endpoints, and evaluation datasets—CI runs faithfulness, toxicity, and jailbreak probes before anything reaches production. Guardrail layers combine regex, classifiers, and LLM judges with configurable escalation to human review.
Dashboards track drift when upstream models change—alerts fire when win rates drop on golden sets, not when Twitter notices first.
02 // ENGINEERING
Development process
Structured phases—from discovery to launch—with clear ownership and handoff points.
Risk taxonomy (weeks 1–3)
MVP (weeks 3–10)
Pilot team (weeks 8–14)
Expand (weeks 12–18)
Operate (ongoing)
03 // CAPABILITIES
Core Capability Matrix
The building blocks of your solution
Datasets
golden prompts; PII-safe fixtures.
Metrics
accuracy; refusal rates; latency cost.
Harness
batch eval; pairwise judging optional.
Guardrails
input filters; output filters; escalation.
Versioning
prompt git; model pins; rollback.
Red team
scenario libraries; scheduled runs.
Compliance
audit log; approval workflows optional.
Integrations
LangSmith-style hooks optional; CI plugins.
API
runtime policy fetch; shadow mode.
RBAC
who can promote to prod.
04 // DELIVERY LIFECYCLE
The strategic roadmap
Milestones and checkpoints—each phase has a clear outcome before the next begins.
Weeks 1–3: Evaluation criteria aligned with legal.
Weeks 4–8: First automated nightly evals.
Weeks 9–14: CI blocking on regressions.
Weeks 15–18: Organization-wide policy templates.
Ongoing: Quarterly red-team exercises.
05 // PRODUCT SCOPING
Choosing your path
Two engagement models—start lean and iterate, or commit to a full platform build from day one.
MVP
Speed & essentialism
Full product
Enterprise maturity
06 // PARTNERSHIP
Why work together
A single accountable partner across strategy, build, and go-live—not a revolving door of vendors.

End-to-end ownership: discovery, architecture, implementation, and launch—with clear communication and production-grade engineering.
- Discovery & alignment
- Systems that scale
- Implementation depth
- Clear comms
07 // CLARITY
Frequently asked
Provider-agnostic harness—OpenAI, Anthropic, Azure, and open weights supported with parity tests.
08 // MORE SOLUTIONS
Related solutions
Federated Learning & Privacy-Safe Cross-Silo Analytics Development
Train and aggregate without centralizing raw data—collaborative ML for hospitals, banks, and device fleets.
arrow_forwardAI Agent Orchestration & Multi-Step Workflow Platform Development
Tool use, human approvals, and traces—agents that complete work without silent side effects.
arrow_forwardCrypto Payroll & Global Stablecoin Payments Platform Development
Earnings, tax withholdings, and on-chain settlement—global payouts where compliance and treasury policy stay aligned.
arrow_forwardReady to start?
Tell me about your product goals and timeline—I'll respond with a clear path forward.