Support triage. Lead qualification. Invoice processing. Content operations. Commerce personalization. We design, ship and operate agentic workflows with real tool-calling, RAG over your data, human-in-the-loop guardrails, evals, and the observability you need to sleep at night.
A chatbot answers. An agent decides, acts and reports. Our agents read from your systems, write to your systems, ask for human approval on the expensive calls, and run under continuous evals so drift gets caught before your customers do.
These are the shapes we've built most often. If your workflow looks like one of these, we can scope it in a single call. If it doesn't, we'll tell you which archetype it's closest to — or that we're not the right shop.
A weekend demo has one or two of these. A thing you put in front of customers has all seven. This is most of the work — and most of what we charge for.
USD, project-based, fixed ceiling. Each tier lists what's in and what's out. Production launches always pair with an Agent Ops retainer — agents without operations degrade in weeks.
We prefer short cycles with visible checkpoints. If something isn't working by the end of step 3, we'd rather tell you than quietly keep billing.
For a demo, yes. For production — where wrong answers cost money or trust — no. The gap between a prompt that works in the playground and an agent that runs reliably in front of real customers is tool-calling against messy APIs, RAG that handles your actual data, evals that catch regressions, guardrails on expensive actions, and ops that keep it tuned as models change. That's the work we do, and it's what the price pays for.
Whichever one wins the evals for your specific workflow. We design model-agnostic where we can so you're not locked in when a cheaper, better option ships next quarter — which, right now, happens every quarter. For cost-sensitive loops we route simple calls to small models and reserve frontier models for the hard decisions.
Four layers. (1) Tool design — irreversible actions are gated behind explicit approval tools. (2) Validators — structured outputs with schema checks before any write. (3) Human-in-the-loop queues — refunds, external sends, financial posts always route to a person. (4) Kill switches and rate limits at the orchestration layer. We'd rather ship a slightly less autonomous agent than a fast one that wrecks a customer relationship.
Yes — that's the default. Code lives in your GitHub org, infra in your cloud accounts (Vercel, Cloudflare, AWS, your choice). We don't lock you into a proprietary orchestration platform. If you want us to host and operate it, the Agent Ops retainer covers that.
We default to provider zero-retention settings, scrub PII at ingest where possible, and keep your data in your region where required. For regulated domains (healthcare, finance, legal) we'll design around self-hosted or VPC-deployed models and document the data flow end-to-end before a single byte moves.
Then we'll say so on the intake call. Plenty of problems are better solved by a deterministic pipeline, a decent search index, a cron job, or just better UX. Agents are a tool — not a religion. We'd rather turn down a bad-fit project than deliver an expensive disappointment.
Both. Our Starter and Feature tiers are priced deliberately for seed-stage and bootstrapped teams who need an agent shipped and operated without hiring an in-house ML team. Vertical Agent engagements tend to be enterprise. We don't add enterprise theatre to startup projects or vice versa.
Thirty-minute intake call, no deck, no sales motion. You leave with a clear answer and, if it makes sense, a one-page spec.