AI assistants that actually do the job.
An AI assistant earns its place when it removes a repetitive task from someone's calendar — not when it dazzles in a five-minute demo. We build assistants that handle the boring 80% of inbound work, hand the tricky cases to a person, and quietly improve as your team uses them.
Where assistants pay off
Customer support triage and first replies. Inbound lead qualification. Operations escalation. Internal Q&A from your docs. Content drafting from briefs. We pick the shape based on what's actually clogging your team — not the buzzword of the week. Most of our assistant builds replace 6–15 hours per person per week.
What we build, in plain terms
A single-purpose AI assistant connected to the tools you already use (Slack, your CRM, your support inbox, your docs). It has a clear job, a clear scope, and a clear handoff to a human when it's unsure. You can read every reply before it goes out, or let it act on its own once you trust it. We always build the human-in-the-loop version first.
How we keep them honest
Every assistant ships with a small eval suite (10–30 real cases your team picks) that runs on every change. Errors and edge cases route to a review queue. We monitor cost, latency, and resolution rate; you see them in a dashboard from day one. When the model improves, we swap it without rewriting the assistant.
Questions teams ask first.
Can you build this on top of our existing CRM/helpdesk?
Yes — we connect to whatever you already use (HubSpot, Salesforce, Zendesk, Intercom, Front, Help Scout, custom). We don't ask you to migrate.
Which AI model do you use?
Whatever the work needs. Anthropic Claude for nuanced replies, OpenAI for tool-heavy flows, open-source Llama or Mistral when you want self-hosted. We choose after we understand cost, latency, and accuracy constraints.
What's the typical timeline?
Two-week discovery sprint, then 2–4 weeks to ship the first production version. Most assistants are handling real traffic within six weeks of kickoff.
If you have a repetitive task and a team that's tired of it, send us the most annoying one and we'll tell you whether an assistant fits.