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Generative AI that survives real users
From copilots to document-heavy workflows, generative AI needs grounding, evaluation, and guardrails—not prompt hacks alone. We help you choose patterns (RAG, tool use, agents), measure quality, and ship features your security and compliance teams can support.
From prototype prompts to production systems
We combine product sense with ML engineering: cost/latency tradeoffs, hallucination controls, and observability for non-deterministic behavior.
Use-case design
Map tasks to the right pattern: summarization, extraction, Q&A, codegen, or agentic flows—with explicit failure handling.
Retrieval & context
Chunking, embeddings, re-ranking, and knowledge updates so answers stay relevant and attributable where needed.
Safety & policy
Content policies, PII handling, access boundaries, and audit-friendly logging aligned to your risk profile.
Evaluation & ops
Offline suites, online metrics, human review loops, and regression tests so changes do not silently degrade quality.
How we help
Advisory through implementation—meeting you at your current maturity.
Architecture assessments
Review stacks, vendors, and patterns; recommend a target architecture with cost and latency models.
Build partnerships
Joint delivery with your engineers: APIs, orchestration, evaluation harnesses, and rollout plans.
Operating model
Roles, prompts-as-code practices, incident playbooks, and governance checkpoints for ongoing releases.
Migration & hardening
Move fragile demos into testable services with CI, monitoring, and rollback-friendly deploys.
Outcomes teams expect
Generative AI projects stall on trust and maintainability. We focus on measurable quality and operational discipline.
- Clear metrics for helpfulness, correctness, and safety for your domain
- Reduced surprise regressions when models or documents change
- Better unit economics through caching, routing, and model selection
- Executive-ready documentation for risk and compliance reviews
Ideal fit
Product and platform teams launching LLM features; enterprises modernizing support, internal knowledge, or developer tooling.
Related services
Combine with integration and MLOps for full lifecycle coverage.
Ship generative AI you can stand behind
Tell us about users, documents, and constraints—we will chart a pragmatic path.