We build AI systems that handle lead triage, customer support, research, operations, and internal tooling — wired into your stack, monitored, and governed by humans.
If humans are doing the same research, triage, or follow-up every day — there's an agent for that.
Inbound leads scored, enriched, routed, and replied to in under 5 minutes. Before your SDR finishes coffee.
Docs-grounded agents resolving 60–80% of tickets without a human. The rest handed off with full context.
Competitive intel, RFP responses, sales-call briefs — drafted from your stack and approved, not written from scratch.
Onboarding, approvals, data cleanup, scheduled reports. Plumbing work humans shouldn't do.
From interview transcript → blog → email → social. Reviewed and published through your existing stack.
Natural language over your warehouse. Slack-native "what happened to conversion yesterday?" — answered.
A battle-tested delivery process. Every agent ships with evals, observability, and human-approval gates baked in — not bolted on.
Workflow mapping, data audit, tooling inventory. We identify the highest-ROI automation and define success metrics before a line of code is written.
↳ Scope doc + eval criteriaFirst working agent on synthetic data. We build the golden dataset and set the eval bar the agent must pass before it touches production.
↳ Working prototype + eval suiteProduction-grade agent wired into your stack — integrations, error handling, retry logic, observability, and human-in-loop approval gates included.
↳ Staged deploy + integrationsLive in production. Runbook, monitoring dashboard, team training, and a 30-day support window. You own the system from day one.
↳ Live agent + runbook"Agents that work while you sleep" still need to be supervised. We instrument every system with approval gates, eval suites, and kill switches.
High-stakes actions (refunds, contracts, emails to VIPs) get human approval until the eval bar is met.
Golden datasets, LLM-as-judge, regressions tracked. No agent ships without a passing scorecard.
Every call traced, every tool use logged. You debug incidents in minutes, not days.
Your API keys, your data boundaries. We don't lock you in — swap OpenAI for Anthropic in one line.
Real timings from production deployments — not estimates. Same workflow, before and after automation.
We build on the best foundation models and orchestration layers — portable across providers, deployable in your cloud.
Book a 30-minute call. We'll identify three candidates with real ROI before we hang up.
It can — and pretending otherwise is how teams get burned. We design for it: scoped tools, strict input/output schemas, evals that run on every change, and human-in-the-loop on anything irreversible. The agent doesn't get to fail in production without somebody noticing.
Yes. We default to deployments inside your cloud (AWS, GCP, Azure) with no data leaving your boundary. Where SaaS LLMs are needed, we use enterprise zero-retention contracts. We sign DPAs and BAAs.
Whichever one is best for the workflow — Claude, GPT, Gemini, open-weight Llama / Qwen, or local Mistral. We benchmark for your task, then build a model-portable layer so you can swap when something better lands.
Eval suites with task-specific scoring (factuality, action correctness, latency, cost-per-task) plus old-fashioned business KPIs (resolution rate, conversion, hours saved). We don't consider a project shipped until the metric moves.
Usually you don't need to — well-prompted retrieval beats fine-tuning for ~80% of business cases. When fine-tuning earns its keep, we do it (LoRA, distillation). We'll tell you which side of that line you're on.