Choose a task for AI and launch a pilot.
The most common question sounds like “we need AI, where do we start”. We answer from the other end: which process hurts, what it costs today and whether the improvement can be measured. Then we pick the minimal scope that tests it and take it to production.
Describe the process you want to start with
What people do today, how long it takes and which systems are involved. We'll tell you whether the task suits a pilot and propose a first version. Timelines and estimates come after the review.
How it works
Find where AI pays off
We look at processes with a lot of unstructured text, repeated judgement calls and manual sorting. That's where the effect is measurable. Elsewhere plain automation is usually cheaper.
A pilot with a measurable outcome
A small scope with a success criterion named up front. Not “let's try AI”, but “in N weeks we look at this specific number”.
Data and privacy
We work out which data can go to an external provider and which cannot, and what follows for the architecture: external model, self-hosted or a hybrid.
From pilot to production
The most common break point: the pilot worked and stayed a slide deck. We plan integrations, monitoring and running cost from the very start.
Pilot example: triaging incoming requests
Suppose a team reads incoming requests and routes them by hand. A pilot can focus on one request stream and test whether AI helps classify and route it while people retain control.
What we need first
Sample requests, the current routing rules and someone who resolves ambiguous cases. Sensitive data is excluded or handled under agreed conditions.
What we build
A working flow for one channel suggests a category and destination, shows the basis for each suggestion and sends uncertain cases to a person. Staff make the final decision during the pilot.
What you receive
A working first version, a decision log and a list of errors found on real examples. We also record processing cost and the integration work needed for the existing system.
How we decide what follows
Before work starts, we agree what counts as correct routing, how many manual corrections are acceptable and which time savings matter. We compare the pilot with the manual process before expanding or stopping it.
This illustrates a pilot structure; it is not a client case. Scope, timing and acceptance criteria depend on your process.
Why us
A measurable result from our practice: in a GeoAI project, the response delay for oil spills went from 6-48 hours to online. Pollution Detection case →
FAQ
Where do we start with AI adoption?
With a process, not a technology. Take one task where people read, sort and make repetitive decisions a lot, and measure how much time it eats. That's your pilot candidate.
How long does a pilot take?
It depends on how accessible the data and systems are. We give concrete timelines after discovery, once the minimal scope is clear. Before that it's more honest not to promise.
Will our data go to an external model?
Only if you allow it. We choose the setup after reviewing your data requirements, including personal-data law. The options: a model hosted by a cloud provider, a self-hosted model on your infrastructure, or a hybrid scheme where only an anonymised minimum leaves your perimeter. We estimate the running cost of each option up front.
Do you handle AI implementation end to end?
Yes, if end to end means one team for the whole path: process review, pilot, integration with your systems, production launch and the next iteration. On your side we need access to data and systems and a person who accepts the result. We don't promise the effect before the pilot: that is what the pilot is for.
How much does AI implementation cost?
It depends on four things: data availability and quality, the number of systems to integrate, quality and acceptance requirements, and model call volume in production. So we review the process and define the first version before giving an estimate. Our article on AI agent cost breaks down where the money goes.
What if the pilot doesn't confirm the effect?
That's a valid pilot outcome — it's what a pilot is for. The success criterion is named up front, so a negative result shows up quickly and cheaply, not a year into operation.
Read also
AI implementation: plan your first business pilot
A first pilot should answer a specific question: can the system complete the chosen task at acceptable cost and quality? Document the current workflow and acceptance conditions before development. Those inputs support a decision to launch, revise or stop.
How much does an AI agent cost?
An AI agent's cost includes development and the ongoing cost of a working process. A model tariff covers only part of that total: integrations, retries, maintenance and human review also matter. Before comparing proposals, define the result you are paying for.
AI agents for business: which tasks to delegate
AI agents for business can help with workflows that involve interpreting text, choosing a next step and using several systems. Start with one process and define its result, permitted actions and acceptance checks. The scenarios and selection table below help you choose a pilot.
AI agent platforms in 2026: what a business should choose
Eleven platforms, what each of them charges for, where its ceiling is and what actually works from Russia. Every figure comes from the vendor's own public page, checked on 6 September 2026, with the source named. No rankings and no top-ten lists: the choice depends on what you are building, not on a position in a table.
Checklist: are your documents ready for RAG
PDF, 2 pages. No sign-up, no email — just the file.