Custom AI agent development for one process, acting inside your systems
We build an agent for one concrete task. It reads incoming data, decides what to do and acts through the APIs of your systems. Every step is logged. Risky or unclear cases go to a person.
What hurts
Your team repeats the same steps every day: open a request, check the data, copy it into the CRM, reply to the customer. These are hours of routine that need no real decisions. When you looked for an AI agent development company, you mostly found chatbots that talk but do nothing.
Off-the-shelf tools do not know your rules and cannot reach your systems. You end up writing the integration yourself, and the result is hard to verify. Nobody is clearly responsible when the agent gets something wrong.
AI sometimes makes mistakes, and that is the real fear. So we set the limits first: what the agent does alone, what it only proposes, and what a person always confirms. Without this, an agent should not touch real customers.
What we build
- Process and decision rules mapped together with your team
- Agent tools: API calls to your CRM, ERP, email and spreadsheets
- LLM reasoning with tool calling and explicit instructions
- Reliable step execution on Temporal: retries, timeouts, queues
- Action log in PostgreSQL: what the agent saw, decided and did
- Handover to a person via Telegram, Teams or a CRM task
- Test cases built from real examples before launch
- Rollout on part of the flow first, then on full volume
What you get
- Source code of the agent and its tools in your repository
- A deployed agent on your servers or ours, with all access handed over
- Documentation: process, rules, limits and an operator guide
- A test suite to run before every change
- A dashboard of agent actions, errors and escalations
How we measure the result
- Share of tasks closed by the agent without a person
- Time from a new task to its completion
- Number of errors found during human review
- Share of escalations and the reasons behind them
Systems and stack
Industries
Questions
How much does a custom AI agent cost?
From $5,000 for an agent covering one process. The price depends on how many systems it connects to, how complex the rules are and your security requirements. After discovery you get a fixed estimate in 2–3 days. If we exceed it through our fault, we finish at our own cost.
How long does it take?
Usually 4–8 weeks. Discovery takes 1–2 weeks, then we build with a demo every week. The agent first works on part of the tasks under human review. Once the metric written into the contract is met, we switch on full volume.
What do you need from us?
A process description or a person who knows it well. Real examples of tasks from recent months. Test access to the APIs the agent will use. We sign an NDA and a GDPR data processing agreement before we receive any access.
Which systems can the agent work with?
Anything with an API: HubSpot, Pipedrive, SAP, Odoo, email, Google Sheets, internal databases. Without an API we set up scheduled file exchange or a separate integration layer. For sensitive data we run our own LLM on our servers, so data does not go to third-party models.
What if the agent makes a mistake?
The agent only proposes risky actions, such as refunds or contract changes, and a person confirms them. Every step is in the log, which makes errors easy to trace. After a fix we add the case to the tests so it does not come back after later changes.
What happens after launch?
Support under an SLA: monitoring, fixes, model and rule updates. You see a dashboard of what the agent does and can check any decision. New tasks are added as separate stages with their own estimate.
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Describe the task. We reply within one business day, the first call is with the founder.
Describe the task. The first call is with the founder.
We reply within one business day. 30 minutes to tell you whether it is worth doing and what it costs.