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.
This direction is preparing to launch
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
160 M ₽ a year lost to controllable causes — price and quoting speed; actual markup ×1.59; two suppliers without VAT — 20% savings on purchasing; a queue of 55 deals waiting for manual costing.
Automated
The robot sees a new deal within 5 minutes, reads the drawing, costs it to within ±6% on a benchmark set of quotes and proposes a sale price — a human checks the 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