AI agents that actually ship - custom-built for your workflows.
We design and operate AI agents that handle real business work: qualifying leads, taking calls, drafting follow-ups, triaging tickets, and running back-office workflows. Production-grade, monitored, and built around your existing CRM and tools.
TL;DR - In one paragraph
AI agents are software that uses a large language model to plan, decide, and act on behalf of a person or team - calling tools, following workflows, and operating with optional human approval. Unlike chatbots, agents do work; they do not just reply. Super In Tech ships production agents in 4-8 weeks with eval suites and monitoring.
An AI agent does work. A chatbot just answers questions.
An AI agent is software that uses a large language model to plan, decide, and act on behalf of a person or team. Where a chatbot only replies, an agent calls tools (search a CRM, send an email, update a record, place a transaction), follows multi-step workflows, and operates with optional human-in-the-loop approvals at sensitive points.
The pattern is straightforward: a goal, a set of tools the agent is allowed to use, data it can retrieve, and a way to measure whether it succeeded. The hard parts are the engineering around the model: the tools, the evaluation, the monitoring, and the iteration loop. That is where most internal builds stall - and where we focus.
Five agent patterns we ship to production.
Voice Agents
Answer inbound calls, qualify leads, book meetings, take after-hours bookings. Includes warm-handoff to humans on edge cases. Reference: HeyAva.
Sales / SDR Agents
Research prospects, draft personalized outreach, follow up across multiple channels, score replies, escalate hot leads to a human rep.
Support Agents
Handle tier-1 tickets end-to-end: identify intent, look up account/order data, draft responses, take action (refunds, replacements) within authority limits, escalate everything else.
Ops Agents
Triage incoming work, classify documents, extract data from invoices and contracts, update systems, and route to the right team. Most common in finance, HR, and back office.
Knowledge Agents
RAG-powered agents that answer team or customer questions from your internal documents, SOPs, and ticket history with proper citations and human review on sensitive answers.
Multi-Agent Systems
Coordinated agents that hand off work to one another - for example, a research agent → a drafting agent → a reviewer agent → a sender. Used when no single agent can fit the whole workflow cleanly.
How we keep agents reliable in production.
The model is the easy part. Reliable agents need engineering around the model. Here is the stack we ship with every build.
Tool schemas (what the agent can do)
Every action the agent can take is a typed function with explicit inputs and outputs. The agent cannot call anything outside this list - so it cannot do something we did not authorize.
Evaluation suites (does it work?)
50-500 test scenarios per agent, run automatically before any production change. We score accuracy, latency, and cost. If a prompt change breaks the eval, it does not ship.
Human-in-the-loop (safety net)
Sensitive actions - refunds over a threshold, legal language, anything irreversible - pause for human approval. We dial the threshold down as confidence builds.
Retrieval (your data, not the model's)
RAG pipelines so the agent answers from your documents, CRM, and history - not its training data. Reduces hallucinations and keeps answers grounded in your reality.
Monitoring (catch problems before users)
Dashboards for eval scores, drift, error rates, latency, and cost. Alerts on regressions. Weekly review of edge cases that fell outside the agent's confidence band.
Iteration cadence (it gets better)
Every agent improves on a monthly cycle: new edge cases get added to the eval suite, new tools get added when patterns emerge, prompts get tightened. The system gets sharper, not stale.
HeyAva - a voice-first AI Chief of Staff.
HeyAva is a voice-first AI agent for executives and small teams. It answers calls, takes meetings, drafts follow-ups, runs daily ops, and escalates only what needs a human. Production system, multi-tool, integrated with calendar and CRM.
Read the HeyAva build →Practical questions about AI agents.
An AI agent is software that uses a large language model to plan, decide, and act on behalf of a person or team. Unlike a chatbot, which only replies, an agent can call tools (search a CRM, send an email, book a meeting, update a record), follow multi-step workflows, and operate semi-autonomously with optional human approval at sensitive steps.
A chatbot answers questions. An AI agent does work. A support chatbot might tell a customer "your order shipped Tuesday" - an AI agent looks up the order in your system, confirms shipment status, opens a refund if shipping is delayed past SLA, drafts an apology email, and routes the case to a human only if the refund exceeds your auto-approval threshold.
Five common patterns: (1) Voice agents - answer calls, qualify, book meetings (e.g., HeyAva). (2) Sales/SDR agents - research prospects, draft outreach, follow up. (3) Support agents - handle tier-1 tickets, draft responses, escalate. (4) Ops agents - triage incoming work, classify documents, update systems. (5) Knowledge agents - answer team or customer questions from your internal docs.
Build cost: USD 6,000 for a focused single-purpose agent, USD 12,000-USD 25,000 for multi-tool agents with CRM integration, USD 25,000+ for multi-agent systems. Operating cost: USD 200-USD 3,000/month depending on volume - most of which is model API spend, not our retainer. We share a fixed-price quote after a free 30-minute discovery call.
A focused single-purpose agent (e.g., a meeting-booking voice agent) ships to pilot in 4 weeks and full production in 6 weeks. Multi-agent systems run 6-10 weeks. We work in weekly demo sprints - you see the agent run live every Friday.
Three layers. (1) Tool-use schemas - the agent can only call functions you have defined and approved (e.g., "send_email" is allowed; "delete_record" is not). (2) Human-in-the-loop on sensitive steps - refunds over $X, legal language, anything customer-facing on a first run. (3) Evaluation suites - we run the agent against a test set of 50-500 scenarios on every change, before production gets it.
Yes. We have shipped agents on top of GoHighLevel, HubSpot, Salesforce, Pipedrive, Zoho, Notion, Airtable, Slack, Gmail, Calendly, Stripe, and many custom internal APIs. If your tool has an API or webhook, we can wire the agent into it.
In our deployments, no. They take over repetitive, well-defined work so your team focuses on the work that needs human judgment. The most successful builds we have shipped pair an AI agent with one person who reviews edge cases - together they handle 4-8× the throughput of two humans alone.
Book a free 30-minute agent design session.
Bring one workflow you wish ran without a human in the loop. We will scope an AI agent for it, benchmark candidate models on your data, and send a fixed-price proposal within 5 business days.