Support agents
Read the ticket, check the order in Stripe or Shopify, then reply or refund within your rules. Hard cases go to a person with a summary attached.
AI Agents
We design, build and run custom AI agents. They connect to your CRM, inbox, docs and databases. Then they plan, act and report back. You stay in control of every move that matters.
An AI agent is software that uses a language model to plan and take actions toward a goal. It can call tools, read data and decide its next step. A chatbot replies to messages. An agent finishes tasks, like closing a support ticket or updating a deal in your CRM.
Signs you are ready
Use cases
Read the ticket, check the order in Stripe or Shopify, then reply or refund within your rules. Hard cases go to a person with a summary attached.
Research new leads, score them against your ideal customer and draft a personal first email. Your CRM stays up to date on its own.
Reconcile invoices, chase missing documents and update records across systems. They run on a schedule or when something changes.
Search the web and your own files, compare sources and write a short brief with links. Useful for market scans, vendor checks and due diligence.
Answer IT and HR questions, reset access and file requests in the right system. Your team gets help right inside Slack or Teams.
Deliverables
Everything ships in your repo and your cloud. You own all of it.
Deployed in your cloud or ours and connected to your real tools.
Secure links to your apps, with only the access each task needs.
Clear rules on what the agent can do alone and what needs a human yes.
Test sets that score every change, plus live views of cost, speed and success rate.
You own the repo. Your team can run it without us.
How we work
Every project runs on the Zap Sprint. A fixed price, a working prototype in about 14 days and a production launch in four to six weeks.
We sit with the people who do the work today. We write down every step, tool and decision.
We choose the model, the tools and the rules. We decide where a person must approve.
We replay past tickets, leads or tasks. The agent must pass before it touches live work.
First the agent drafts and people approve. When the numbers hold, it acts alone on safe tasks.
By industry
Case study
A chatbot answers questions. An agent takes actions. It can look up an order, issue a refund, book a meeting or update a record. It does this inside limits you set.
Yes. We connect agents to the tools you already use. Think HubSpot, Salesforce, Zendesk, Intercom, Slack, Google Workspace and Microsoft 365. Your own databases and APIs work too.
We limit what each agent can access. We add approval steps for risky actions. We test it on hundreds of past cases before launch. After launch we log every action and score quality every day.
A focused agent usually reaches a working prototype in 14 days and production in four to six weeks. Agents that touch many systems take longer, so we split them into phases.
It depends on the job. We often use LangGraph, the Claude Agent SDK or the OpenAI Agents SDK, with MCP for tool access. We pick what fits your stack and your team.
Related services
Got a messy process?
Tell us what slows your team down. We will show you what an agent could do about it. The first call is free.