When a team needs to review ten annual reports, twenty contracts, or a stack of due diligence documents, the standard approach is to read through each one manually and try to hold the answers in their heads or across a growing set of notes. That process is slow, inconsistent, and easy to get wrong, particularly when the same questions need to be answered across every document in the set.
The Evidence Base is Qonera’s answer to that problem. It is a structured grid for running the same set of questions across many documents at once, with every answer sourced, reviewed, and ready to sign off on before it leaves the team.
You start by uploading the documents you need to analyse: a set of 10-Ks, a group of supplier contracts, a stack of policy documents, a collection of research reports. Then you define the questions you want answered across all of them. What was revenue? What are the stated risk factors? Does this contract include a termination clause? What market size does this report cite?
Qonera runs those questions across every document in parallel. The result is a grid: documents on one axis, questions on the other, and an answer in every cell drawn directly from the source material, with a page citation so you can see exactly where it came from.
A summary tells you what an AI decided to include. A grid shows you the answer to your specific question, for every document, side by side. That is a different and more useful thing.
When you can see that one filing reports revenue growth of 38% and another reports 21% for the same period, that conflict is immediately visible. When one contract has a limitation of liability clause and another does not, the gap shows up without anyone having to manually search for it. When a risk factor appears in nine out of ten reports, the pattern is clear in a way it never would be from reading each document in isolation.
Every cell is reviewable. When you click one, a detail panel opens on the right showing the full extracted answer, the evidence quote pulled directly from the document, the citation, and a trust signal at the top of the panel. That signal tells you what the models found: high confidence where the evidence is clear and the models aligned, mixed evidence where the source material is partial or ambiguous, and models disagree where the three independent models reached different conclusions on the same passage.
The panel also shows a breakdown of how each model responded individually, so a reviewer can see not just the final synthesised answer but what each model contributed to it. If the answer needs correcting, it can be overridden directly from the panel.
Above the grid, a row of summary cards shows the state of the review across the full document set: how many cells have been approved, how many have been flagged for closer attention, and how many are still being analysed. Flagged cells are highlighted in the grid so they are easy to find, and reviewers can work through the matrix systematically without losing track of where they are.
The Evidence Base is not a report generator. It is a structured review tool. The grid is designed to be worked through before anything leaves the team. A named supervisor reviews the answers, checks the citations, investigates the cells that need attention, and signs off. That sign-off is recorded, with a full audit trail of who reviewed what and who approved the final output.
The alternative is reading every document manually and trying to stay consistent across the full set, with no record of what was checked or who made the call. The Evidence Base makes that process structured, traceable, and reviewable instead.
The most common use cases are situations where the same questions need to be answered across a large set of documents. Investment teams running analysis across a group of company filings. Legal and compliance teams checking contracts for specific clauses. Strategy teams pulling the same data points from a set of competitor reports. Due diligence teams working through a document room without missing questions or losing track of which documents have been covered.
In each case the core problem is the same: too many documents, the same questions, and no good way to do it consistently. The Evidence Base is built for exactly that.
Multi-model stress testing, Conflict Heatmap, tamper-evident audit trail, and structured sign-off, built for teams who need defensible AI output.