/services
One category, built properly: production AI.
We build and run AI agents and features that take real action — under one roof, to one engineering bar. Guardrails, evals, monitoring, and code you own on every engagement.
AI Support Agents
Most “AI support” only answers questions. A real support agent looks up the customer, applies your policy, and takes the action like refunds, account changes, status then escalates cleanly when a human is genuinely needed.
What you get
- Tier-1 tickets resolved end-to-end, not just acknowledged
- Refunds, account changes, and lookups taken as real actions
- 24/7 coverage that sounds like your product, not a generic chatbot
- Clean escalation with full context when a human is needed
How we build it
- Retrieval
RAG over your docs and policies, with citations on every claim.
- Actions
Tool calls into Stripe, your database, and your help desk (Intercom, Zendesk, Front).
- Guardrails
Confidence thresholds, action allow-lists, and confirmation before anything irreversible.
- Evals
Scored against your historical tickets in shadow mode before it touches a customer.
Ticket #4821
Duplicate charge · Pro plan
Customer · 10:01
Support agent · 10:02
Behind this reply: looked up cus_Pf21Qa · matched 2 October charges · refund ch_3Pdup $49 · closed without escalation
AI Voice Agents
Demo requests come in at 11pm. Trial users want to speak to someone before they convert. Inbound calls hit when your team is on a flight. A voice agent answers on the first ring, qualifies the intent, and books the slot. So the call doesn't disappear into voicemail.
What you get
- Every inbound call answered, day or night
- Callers qualified and booked into your calendar
- Confirmations and follow-ups sent automatically by SMS
- Warm transfer to a human the moment it matters
How we build it
- Pipeline
Low-latency STT → LLM → TTS over Twilio, with natural turn-taking and barge-in.
- Actions
Calendar and CRM tool calls — Cal.com, HubSpot, Salesforce.
- Guardrails
Intent capture checks, fallback phrasing, and instant human handoff paths.
- Evals
Full transcripts plus scoring on booking accuracy and intent capture.
Inbound · +1 (415) ***-4821
1:47 · intent: schedule consultation
Caller · Do you have availability this week for a consult?
Agent · Thursday at 2pm or Friday at 10am — which works? I'll text a confirmation once we're set.
Caller · Thursday at 2 works.
Thu 14:00 booked in Cal.com · SMS confirmation sent · CRM note filed
AI Feature Build
You have an LLM / RAG / agent feature your product needs — and a team already at capacity. We build it to production standard, integrated into your stack, with evals you can run yourself, and code you own.
What you get
- The AI feature on your roadmap, actually shipped to production
- Grounded answers with citations — engineered against hallucination
- Built into your product, your stack, and your design system
- Owned by you, with an eval suite you can run on every change
How we build it
- Pipelines
RAG, agents, and structured-output systems in TypeScript or Python.
- Retrieval
Vector store tuned to your data — Pinecone, pgvector, or your stack.
- Eval harness
Faithfulness, accuracy, and latency budgets wired into CI.
- Deploy
On your infrastructure (Vercel, AWS), observable end-to-end.
answer-pipeline · CI eval
run #284 · 142 cases
| Suite | Result | Gate |
|---|---|---|
| Faithfulness | 97% | pass |
| Citation accuracy | 94% | pass |
| Refusal rate | 100% | pass |
| p95 latency | 1.2s | pass |
retriever.search(q) → llm.generate(context, guardrails) → citeSources