Generative AI Solutions_

Production is the bar. We build LLM integrations, RAG pipelines, voice agents, and multi-agent workflows with guardrails, observability, rate limits, and failure modes designed in. Proven at 1.5M+ calls/month with ≈2.5s voice latency, not slideware prototypes.

We treat model output as untrusted until validated. That means PII detection and redaction (proven at >98% accuracy on our systems), human-in-the-loop where risk is high, citation-backed retrieval for grounded answers, ARTKit-style red-teaming, and audit trails your compliance team can defend.

No. We design provider-agnostic orchestration so you can swap models as cost, latency, or policy changes. The durable asset is your data contracts, evaluation harness, and guardrails, not a single API key.

Yes. Delivery patterns cover GDPR, HIPAA, and enterprise security reviews: data isolation, access control, logging, and retention that procurement can approve. If your threat model is stricter, we scope that into architecture before the first feature ships.

Depends on data readiness and risk surface, not hype. Thin production slices often ship in weeks when scope is crisp: one high-value workflow, measurable acceptance criteria, and observability from day one. We refuse “AI everywhere” programs that never clear a go-live gate.

Cost is a product requirement. We instrument usage, set rate limits and budgets, cache where safe, and choose models by task, not by brand. You get unit economics you can manage, not an unbounded sandbox bill.