Agents that take action inside your systems, not chat demos. Built and deployed in weeks.
Overview
"AI agent" gets used to describe everything from a chatbot widget to a fully autonomous system, and most of what gets built under that label never leaves the demo. It answers questions convincingly and does nothing else.
A real AI agent plans a task, calls the tools it needs, takes an action inside your actual systems, checks the result, and knows when to stop and ask a human. That's a meaningfully harder engineering problem than a chatbot, and it's the only version worth paying for.
At Bocati Solutions, we build AI agents that are wired into your CRM, inbox, accounting software, or internal tools from day one, with explicit guardrails on what they can do autonomously and what needs your sign-off. Delivered in weeks, using the same AI-accelerated development process behind our custom software and automation work.
If you've looked at "AI agent" services and come away with a lot of strategy slides and no working software, this is built for the opposite: a scoped agent, a fixed price, and something running against your real data inside a few weeks.
An AI agent plans and executes multi-step work, not just single responses. Here's what we build most often:
Reads inbound email, classifies intent, drafts or sends responses, and routes anything it's not confident about to a human. Cuts response time without losing control of tone or accuracy.
Answers customer questions grounded in your actual documentation, order data, or knowledge base, not a generic model guessing. Escalates cleanly when it hits the edge of what it knows.
Reads incoming invoices, forms, or reports and enters them into your CRM or accounting software, flagging discrepancies for review instead of entering them silently.
Pulls data from multiple internal and external sources, compiles it into the report your team currently spends hours building manually, on a schedule or on demand.
Sits inside your internal tools and answers "what's the status of X" or "who's behind on Y" questions instantly, pulling live data instead of someone checking three systems.
Coordinates a multi-step process across several systems — for example, qualifying a lead, updating the CRM, and triggering an onboarding sequence — with a human approval gate wherever the stakes are high.
Every project starts with a clear scope and a fixed price. No hourly billing, no scope creep, no nasty invoices.
We map the exact task end-to-end: what triggers it, what data it needs, what "done correctly" looks like, and where a human must stay in control.
A defined scope and fixed price before any build starts. No open-ended "AI strategy" retainer.
Working agent on a staging environment every week, tested against real (anonymised where needed) data from your business, not synthetic demo data.
We deliberately try to break it: bad inputs, ambiguous requests, edge cases. The agent needs to fail safely, not confidently do the wrong thing.
Goes live with logging so you can see exactly what the agent did and why. Full documentation and handover — you own it outright.
Pricing guides and real-world insights to help you plan your project.
Technically yes — the underlying models and frameworks are publicly available. In practice, most businesses don't have in-house AI engineering capacity to design the guardrails, tool integrations, error handling, and security review a production agent needs. DIY agents built from tutorials tend to work in a demo and fail quietly in production. That gap is what a development partner closes.
A single-task agent typically runs $8,000–$18,000 over 2–3 weeks. A multi-step agent integrated with your existing systems runs $18,000–$45,000 over 4–7 weeks. A multi-agent platform with monitoring and human-in-the-loop workflows runs $45,000–$90,000+ over 8–12 weeks.
A chatbot answers questions in a single turn. An agent plans and executes multi-step tasks — it reads data, calls tools, takes an action, checks the result, and decides what to do next, within guardrails you define.
Every agent is scoped with explicit permission boundaries: what it can read, what it can act on autonomously, and what needs human approval first. Agents run on your own infrastructure and accounts, not a third-party black box, so every action is auditable.
Business automation typically means rules-based workflows: if X happens, do Y. AI agents handle work that doesn't fit a fixed rule — where the agent has to read unstructured input, make a judgment call, and choose the right action from several options. Many projects use both together.
Get started
Tell us what you need. We will come back with a clear scope, timeline, and fixed price, usually within 48 hours.