Your data already knows everything
We read a company's CRM, mail and documents — and within days turn them into an honest picture of the business: where money leaks, what the real margin is, which supplier is actually cheaper. Then we automate what we found.
First pilot in operation
Data instead of interviews
A classic audit interviews the staff and collects opinions. We connect to what the company has already accumulated — CRM deals, years of correspondence, quotes, invoices, drawings — and reconstruct the process as it actually is. How long a deal lives, at which stage it dies, what the margin really is, what terms each supplier offers.
Findings do not stay in a report: bottlenecks are closed right away with automation — bots, costing pipelines and monitoring on our own infrastructure. In the first pilot a manufacturing company got a year's worth of analytics and a working costing robot within a day.
What we do
Four products — from an honest picture to a running loop. Each works alone; in order they work harder.
Data-driven audit
We connect to the CRM and mail, machine-read everything and hand back an as-is map of the process: the funnel, deal velocity, graveyard stages, lost money traced to its cause.
Operational analytics
Actual margin per purchase-sale pair, supplier dossiers with terms recovered from correspondence, revenue concentration by customer, reconstructed pricing formulas.
Automating the findings
Bottlenecks get closed right away: bots in work chats, automatic costing from documents and drawings, price and supplier recommendations. On our infrastructure, with no changes to your systems.
Live monitoring
The loop stays with you: CRM events reach the messenger within minutes, the price and precedent base grows by itself, accuracy improves on your corrections.
First pilot: 24 hours
A manufacturing company, custom metalworking. From first access to a working robot in a day.
Read
4,261 CRM deals, ~3,800 emails over a year, quotes in spreadsheets and scans, drawings from enquiries. Not a single interview.
Found
The original August 2026 dataset contained lost deals worth about RUB 160 million, with recorded loss reasons related to price and calculation speed; an actual markup of ×1.59; and 55 deals awaiting manual estimates. This is CRM history, not verified savings from implementation. Supplier terms, including VAT, require separate comparison.
Automated
The system receives new deals from the CRM, reads drawings and drafts estimates of cost and selling price. Calculations for this project are being calibrated against manufacturing specialists’ answers; a person reviews each draft.
Let's see what your data knows
Read access to the CRM and mail is all it takes to start. First numbers within days, not a quarter.
Discuss a project