Assessment at a fixed price — credited toward your pilot.
Example: a verified answer
Which orders have been stuck in “Awaiting payment” for more than 5 days?Which orders have been stuck in “Awaiting payment” for more than 5 days?
Three orders match. The oldest has been waiting 9 days.
Order 104829 days
Order 105177 days
Order 105336 days
Source found
Access rights
Control set passed
Action: send reminders needs approval
Sent 3 reminders · Logged · Approved by you
We implement AI the way we build IT infrastructure
Securely, inside your systems, with results you can verify. One integrator covers consulting, infrastructure, cybersecurity and integration with your business systems, so accountability never gets split between vendors. We agree on metrics and a test question set with you before work starts, and how much autonomy AI gets depends on what a mistake would cost.
Why AI pilots stall before they pay off
Many AI projects get stuck somewhere between a good demo and everyday use. The model itself is rarely the reason. What stops them is unclear goals, data scattered across systems and people’s heads, acceptance with no criteria, and teams nobody trained.
42%42%
of companies abandoned most of their AI initiatives before production in 2025, up from 17% a year earlier.1
70%70%
of AI implementation challenges stem from people and processes, according to BCG; 20% from technology and only 10% from algorithms.2
6%6%
of McKinsey respondents are AI high performers, attributing at least 5% of EBIT to AI and reporting significant impact.3
46%46%
of AI proofs of concept are scrapped by the average organization before they reach production.1
One-on-one sessions for business owners and founders. Together we work out how AI can take routine work off your plate and bring order to your business and your thinking.
We walk through your processes, business systems and what you expect from AI.
What you get
2–3 candidate processes and a clear next step.
To move on
We’ve found a process where AI can deliver a measurable result.
Stage 1 of 5 · 60 minutes
We review your processes, data, systems and security requirements. The price is fixed, quoted after the consultation and credited toward the pilot.
What you get
A readiness report, a process for the pilot, metrics and a test question set built from your own examples.
To move on
You’ve signed off on the metrics and the test set. The assessment may honestly conclude that AI isn’t needed here.
Stage 2 of 5 · About 2–3 weeks
We run AI on one process. While the pilot runs, AI changes nothing in your live systems.
What you get
A working pilot and an acceptance report.
To move on
The pilot has passed acceptance against the agreed metrics and test set, including traps for made-up answers.
Stage 3 of 5 · About 4–6 weeks
We roll the solution out to other processes and departments and train the team on its own tasks.
What you get
AI in the daily work of several processes, plus guidelines and an AI use policy.
To move on
Every new process goes through its own acceptance.
Stage 4 of 5 · On a plan agreed after the pilot
We monitor answer quality and request costs, and update the knowledge base as your processes change.
What you get
A regular report on quality and spend.
To move on
Quality and cost stay within the agreed limits. If they don’t, we pause changes and fix it.
Stage 5 of 5 · Ongoing
We walk through your processes, business systems and what you expect from AI.
What you get
2–3 candidate processes and a clear next step.
To move on
We’ve found a process where AI can deliver a measurable result.
We review your processes, data, systems and security requirements. The price is fixed, quoted after the consultation and credited toward the pilot.
What you get
A readiness report, a process for the pilot, metrics and a test question set built from your own examples.
To move on
You’ve signed off on the metrics and the test set. The assessment may honestly conclude that AI isn’t needed here.
We run AI on one process. While the pilot runs, AI changes nothing in your live systems.
What you get
A working pilot and an acceptance report.
To move on
The pilot has passed acceptance against the agreed metrics and test set, including traps for made-up answers.
We roll the solution out to other processes and departments and train the team on its own tasks.
What you get
AI in the daily work of several processes, plus guidelines and an AI use policy.
To move on
Every new process goes through its own acceptance.
We monitor answer quality and request costs, and update the knowledge base as your processes change.
What you get
A regular report on quality and spend.
To move on
Quality and cost stay within the agreed limits. If they don’t, we pause changes and fix it.
How AI works safely in your company
Three rules we agree on before work starts: how much autonomy AI gets, which tasks stay with people, and where your data is processed.
The level depends on the consequences of an action, not on how complex it is. We start low and raise the level only after acceptance.
Reads, summarizes and flags anything unusual. Changes nothing in your systems.
Example
Every morning, compiles a summary of overdue payments with links to the documents.
Drafts an email, a document or a decision. A person has the final say.
Example
Drafts a reply to a customer, which a manager edits and sends.
Takes an action in the system only after the responsible person has approved it.
Example
Prepares a supplier order that the purchasing lead posts after checking it.
AI handles it alone
Search, classification, summaries and drafts, where a mistake is easy to spot and fix.
Under human control
Anything that changes data, money or commitments to a customer. AI prepares, a person approves.
Not for AI
Decisions a person or the law is accountable for, and tasks with no verified data behind them. We say so and leave them to people.
We choose where data is processed based on how sensitive it is. Zero data retention at the provider doesn’t mean the data is processed in the EU. EU companies also need the right region, a contract with the provider and a GDPR assessment.
Data
Where it runs
Why
Public data
Cloud models
The disclosure risk is minimal, so we pick the model that fits the task.
Internal documents and operational data
Cloud models behind a gateway
The gateway logs requests, masks sensitive fields, enforces cost limits and runs on enterprise terms.
Sensitive data: personal data, trade secrets
Private cloud or local models in your own infrastructure
The data never leaves an environment you control.
AI readiness check
Five questions about your goals, data, team and security requirements. We’ll show you where it makes sense for your company to start.
Question 1 of 5
What matters most to your business right now?
Where does knowledge about your processes live?
What do your data and systems look like?
How ready is your team?
How sensitive is the data you work with?
Your first step
We’ll give you a more precise plan after a free 60-minute consultation.
A demo on generic examples and a promise of results.
Metrics and a test question set built from your examples, agreed before work starts.
Made-up answers
Treated as unavoidable, or expected to disappear once there’s a knowledge base.
Acceptance includes traps for made-up answers, and every answer links to its source.
Data
Documents go into AI as they are, in one big folder.
Knowledge lives in a versioned store, and every fact is labeled as verified, reported or inferred by AI.
Business systems
AI sits in a separate chat, and data gets copied in by hand.
We work with your ERP, CRM and core systems, including customized ones. We connect through standard channels, and at the start AI changes nothing in your systems.
People
A one-off training session after launch.
Training on your real tasks. A person approves every action that affects data, money or customers.
Paying for stages
A budget for the whole project up front.
The fixed-price assessment is credited toward the pilot. Each stage starts only after the previous one passes acceptance.
Projects
Trading company, EU (import and distribution)
In progress
Task
A customized business system where about 80% of the process logic lives in the settings of an in-house workflow engine rather than in code. All the know-how sits with one external specialist, and an earlier attempt to feed the configuration to AI as a flat folder produced made-up answers.
What we did
Structured interviews with the owner area by area, a map of what is known and unknown, and a register of the system’s real objects with source labels. The model works with a copy of the system kept apart from the live one, and automated checks catch invented commands.
Result: Acceptance was defined before the start: 8 blind tests, including a trap for made-up answers that must be passed 5 out of 5 with no partial credit.
Understand where the ad budget was going and speed up lead capture.
What we did
An AI audit of advertising, AI-built landing pages and a lead bot.
Result: The audit found that 83% of the budget went to a goal that doesn’t track leads. The new landing pages and bot brought in 4 leads in the first 24 hours.
The consultation takes 60 minutes, the readiness assessment about 2–3 weeks, and a pilot on one process about 4–6 weeks. The exact schedule depends on the state of your data and system access, and we confirm it after the assessment.
The consultation is free. The assessment has a fixed price that we quote after the consultation, and its cost is credited toward the pilot. After the assessment we quote a fixed price for the pilot, and you know the cost of scaling before it starts.
No. SENSETI takes care of infrastructure, security and integration. On your side, we need a process owner who knows how things work and someone who can grant access.
We choose where the model runs based on how sensitive the data is, up to local models in your own infrastructure. AI is developed on isolated copies with read-only access to production systems, and a person carries any changes over. Access rights apply at the search stage, so no one gets anything through AI that they can’t already see in the system.
Your ERP, CRM and core business systems, including heavily customized and legacy setups where the logic lives in configuration rather than code. We also work with documents, email, spreadsheets and call recordings.
The assessment may honestly conclude that AI isn’t needed, and you get a report explaining why. Likewise, a pilot that fails acceptance never moves on to scaling.
The practice is led by Andrii, Head of AI for Business. SENSETI specialists in infrastructure, cybersecurity and integration join the project, and on your side we work with the process owner.
Contact Us
Send a message to our team to find out how we can help you
A
Andrii
Head of AI for Business
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