Main analysis conclusion
Each analysis starts with a management answer, not a table: what it means for the decision. Below are the map, exceptions, and matrix the conclusion is built from.
Trust mechanics
Four layers under every conclusion
A skeptic checks not only conclusions, but how they were produced. That is why every layer is open: from management answer down to raw material and methodology.
How every number is calculated
Under every chart there is an evidence table. Clicking a number reveals which mentions produced the metric and how it was calculated: stability, seasonality, confidence.
Down to raw material: source library
7,500+ sources with trust score and evidence weight. Any conclusion can be unpacked down to the specific fragment it was built from, with source-trust evaluation.
Methodology and limitations
Every analysis has an open methodology: what was calculated, from what, and where the limits of applicability are. Honest limitations instead of polished promises.
How it looks
Evidence screens from a live project
Chart + table underneath
Seasonality of each need by month: click a need for profile and sources, click a number to see how the metric was calculated.
7,500+ sources with trust score
Corpus assessment: strong sources, evidence weight, freshness and reliability map. Customer materials are connected as a separate layer.
Conclusions with coverage
Industry frame with match scoring across 9 axes, opportunities and risks — it is clear what each conclusion stands on.
Against the black box
How this differs from an AI essay
Typical AI answer
- Text without sources cannot be verified
- You cannot prioritize: everything sounds equally confident
- You cannot cite it to the board or council
- Training has a cutoff, so data ages
Segmentable
- Every number clicks through to a source with trust score
- Plays are ranked by Revenue / ROI / Share
- Exec summary and PDF contain the same sources
- Open data is gathered at project time and refreshed
For decision defense
- Exec summary and PDF. The executive summary and report are assembled from project data, with the same sources inside.
- Board presentation. Slides are built from live data: the number on a slide matches the number in the system and its source.
- Security-clean setup. Only external open data — nothing is taken from your perimeter. An argument for security review.
Segmentable research before launch aligned very well with what we later found in in-depth interviews after release.
Press: GTM strategy for Laser Systems JSC and GigaChat — Interfax →
Test evidence on your own market
Build a project and click any number: analysis → table → source. Skeptics like this part most.
Where next
Go deeper
Frequently asked questions
What does “every number clicks through to its source” mean?
Every conclusion links to its primary source: a page, a review, a publication. Verification takes seconds — nothing has to be taken on faith.
Where does the data come from?
From open market sources: company websites and materials, customer reviews, job postings, media, catalogs. Nothing private or personal.
How complete is your data?
Coverage is visible in every project: how many sources were collected and of what type. If a market has little data, you see it before relying on conclusions.
Can the system be wrong?
It can, like any method. The difference is that errors can be found: sources are open, calculations traceable. Unverifiable confidence is more dangerous than verifiable imprecision.
Glossary
- Open market data
- The public traces every market leaves: company websites and materials, customer reviews, job postings, media coverage, catalogues. We collect only what is available to anyone online.