Most teams have generic chat copilots that summarize content. We build agents that actually do the work — read your inbox, run your CRM, ship code, and close tickets. Production-grade, observable, with safety rails on every step.
We pick the right model per task — frontier APIs, fine-tuned open-weights, or hybrid. No vendor lock-in.
Eval harnesses, prompt-injection defenses, PII redaction, and human-in-the-loop wherever it matters.
Working prototype in 2 weeks, production deployment in 4–8 weeks. Weekly demos so you steer.
Every agent ships with metrics — cycle-time saved, deflection rate, $/task. We instrument the win.
We map the workflow you want to automate. Score it on ROI, risk, and feasibility before building anything.
Pick the model, vector DB, and orchestration layer. Lock the eval set so we know when we're done.
Iterate weekly. Adversarial testing for prompt injection, PII leakage, and tool-misuse. No surprises in prod.
Ship with monitoring. Track cost, latency, win rate. Quarterly model migrations baked in.
AI customer-support agent for a B2B SaaS handled 73% of tier-1 tickets autonomously. Headcount reallocated to product work, not support backfill.
RAG-grounded sales-research agent shipped from spec to working demo in two weeks. Closed three enterprise deals on the back of the demo.
Cost-aware prompt design + GPT-3.5/GPT-4 mixed routing kept per-call cost under the unit-economics ceiling. Same quality as a GPT-4-only build at 4x the price.