AI Agent Development
We build AI agents that carry real work in production — answering calls, moving records between systems, filling pipelines — each one designed around a written boundary of what it may decide. The named way in is the Agent Pilot in 30 Days: one process, one agent, one measurable number, from a team that has served 200+ clients across ten years.
The free 30-minute session maps where an agent would actually pay in your operation — volumes, systems, cost per action — and says honestly if the answer is plain automation instead. You keep the notes either way.
Where agent projects actually stand today
Most companies are somewhere between a demo that impressed everyone and a rollout nobody signed off. These are the situations we walk into.
The demo was great; production never came
Someone built an agent in an afternoon with a no-code tool and it wowed the room. Then came the questions that decide production: what happens on the malformed invoice, who is accountable for the wrong answer, where is the log. The demo had no answers, so it stayed a demo.
The team is drowning in work an agent should carry
Copying records between the CRM and the project tracker, triaging inbound requests, chasing status updates — hours of paid attention spent on work with rules. The rules are exactly what an agent needs; nobody has written them down yet.
Nobody can say what the agent may decide
Legal and operations both hesitate for the same reason: the vendor cannot state where the agent stops. An agent without a written boundary is an incident on a schedule. With one, it is a system your auditors can read.
The ROI question keeps killing the budget
Every quarter the idea comes back, and every quarter it dies on “what exactly do we get?”. The honest answer is a number — cost per handled action against cost per human action — and it takes a scoped pilot, not a bigger meeting, to produce it.
Every agent starts as one page of writing: what it decides, what it drafts, what it never touches. The build is the easy half.
What we build, concretely
Agents that act across your systems
Multi-step agents that read from and write to the tools you already run — CRM, email, project management, billing — with idempotent actions and full logs, so every step can be replayed and audited.
You get: the agent, its integrations, and a log a human can read.
A written decision boundary
Before anything runs, we write what the agent may decide alone, what it drafts for a human, and what it must never touch. This single page is what turns an experiment into something operations and compliance will sign.
You get: the boundary document, approved by your owner of the process.
Measurement built in from day one
Cost per handled action, escalation rate, error rate against the human baseline. The pilot is judged on these numbers — and so is the decision to scale it, change it, or switch it off.
You get: a dashboard view of the numbers the pilot is accountable to.
Handover and escalation paths
Every agent has cases it should not handle. We design the handoff — to a named person, with context attached — so the failure mode of the agent is a clean escalation.
You get: escalation rules wired into your existing channels (Slack, email, phone).
How it works
Scope the pilot
Pick the one process where the numbers are clearest. Write the boundary, agree the metric, get the data access sorted.
Build against real data
The agent is developed on your actual records and edge cases, not synthetic happy paths. Integrations land behind feature flags.
Run supervised, then measure
The agent runs with a human reviewing its actions, then progressively alone where the boundary allows. The metric is read out honestly.
Decide on the number
Scale it, adjust it, or stop — the pilot ends in a decision, not a lingering experiment. Scaling continues on a monthly model.
Judged on a number, kept only if it pays.
Proof, not claims
We run agents on ourselves before we sell them — the same discipline of boundaries, logs and numbers applies to the systems below.
The agent that fills our own pipeline
A multi-step agent that researches, qualifies and drafts outreach for our own business development. We are its operator and its customer — the strongest test of the boundary-and-metrics discipline we sell.
A digital employee with strict data boundaries
Precise algorithms, efficient token use, and secure non-AI database integrations — the model never touches the system of record directly.
An Agent Pilot takes 30 days: one process, one agent, one measurable number — judged on the number, kept only if it pays.
“A true professional from beginning to completion. Georgiy pays close attention to details and if very knowledgeably programmer. I would recommend anyone with programming needs to give Georgiy an opportunity and you will not be disappointed.”
The LinkedIn Lead Builder fills our own pipeline every week. We run our agents before we sell yours — same boundaries, same logs, same numbers.
Start with the Agent Pilot in 30 Days
One process, one agent, one measurable number — scoped in writing on the call, priced before anything starts, judged on the number at day 30. If plain software automation would serve you better, we say so on the first call and you keep the analysis.
A 30-minute working session with an engineer, not a sales call. We map the process, the systems it touches and the number a pilot would be judged on. You keep the notes either way.
Clients also buy
Voice AI Agents
Phone, support and sales calls answered 24/7 by a voice agent that knows your business and hands off cleanly.
AI Business Process Automation
From Zapier/Make/n8n hacks to production automation — pipelines that survive volume, audits and staff turnover.
AI Strategy Consulting
A fixed-price consulting engagement, payable online: from "we should use AI" to a costed, buildable plan your board can approve.
The questions that decide production are boring: the malformed input, the accountability, the log. Our agents arrive with those answers written down.
The questions buyers actually ask
What is the difference between an agent and a chatbot?
A chatbot answers; an agent acts. Chatbots retrieve and explain your knowledge — agents log into systems, move records, send messages and complete multi-step work under a written boundary. If your need is answering questions from your documentation, our Chatbots & RAG service is the cheaper right answer.
How do you keep an agent from doing something it should not?
With a written decision boundary agreed before development starts: what it decides alone, what it drafts for human approval, what it never touches. Technically that is enforced with scoped credentials, idempotent actions, full logging and escalation paths — not with hope.
What does an Agent Pilot cost?
It is scoped in writing and priced on the first call, because the number depends on the systems the agent must touch and the data access involved. The pilot is deliberately sized so the decision at day 30 is easy to make on the metric alone.
Which models and platforms do you use?
The ones the job needs. We work with the leading commercial models and open-source alternatives, and the boundary document states what data may reach which provider. The architecture is designed so a model can be swapped without rebuilding the agent.
What happens after a successful pilot?
Scaling runs on a monthly model: more processes, more integrations, and the operational care an agent in production needs — monitoring, drift checks, boundary reviews as your business changes.
Can you fix an agent another team built?
Yes — that usually starts with a short audit of its boundary, logs and failure modes, then a rebuild of the weakest parts. It is the same take-over discipline our Product Rescue service applies to full products.
What AI can actually carry in your business — the one-page version
The nine AI & Agents services on one printable page: what each one is, the situation it answers, and the first engagement that proves it. Built to be forwarded to whoever holds the budget.
Thirty days from scope to a number
Book the free 30-minute session and we map the one process where an agent would pay first — or write two sentences about the work your team repeats every day, and an engineer replies in one business day.
- 30 minutes, an engineer on the call
- You keep the written notes either way
- Nobody follows up more than once
