PDF, Word, text and CSV
All plansUpload filings, contracts, CIMs and data exports as PDF, DOCX, TXT or CSV.
Anweshna takes a deal document from upload to a ranked list of risks, with the quotes and figures behind each finding checked against the source. Here is what it does, and which plans include it.
Before scoring
Upload in the portal, over the API, or from an AI agent. However a document arrives, it is screened the same way and counts against the same plan.
Uploading over the API →Upload filings, contracts, CIMs and data exports as PDF, DOCX, TXT or CSV.
Upload up to 25 files at once, screen them together, and follow each file’s status as it goes.
Use the web portal, call the REST API, or let an agent in Claude or ChatGPT screen documents over MCP.
When a deal room has no industry set, each document is classified and scored against the matching ruleset: M&A, banking, pharma or aviation. The report says when a ruleset was picked this way, so you can confirm it.
Scoring
Each document is scored 0–100 in every category of one industry ruleset: M&A (15 categories), banking (8), pharma (7) or aviation (6).
How scoring works →Financial, legal, HR, sanctions and AML, merger control, IP, AI governance, data privacy and more. See each category.
Seven categories can block a deal. If any one of them scores 70 or above, the deal is flagged for mandatory review, however clean the rest looks.
One close read of the whole document, for contracts and filings up to 130,000 characters of text.
A 300-page filing isn’t cut to fit. It’s split into chunks and every chunk is scored. 25 a month on Growth, unmetered on Pro and Enterprise.
Social security numbers, card numbers, emails and phone numbers are redacted before text reaches the AI model. Company and person names stay, because sanctions screening needs them.
After scoring
A score tells you where to look. The findings show why, quoting the document they came from, so your team spends its time confirming rather than searching.
Accuracy & benchmarks →Quotes and figures in each finding are matched back to the document text. A finding whose quote can’t be found is marked unverified, not quietly kept.
Findings become a list of what to verify, most urgent first and grouped by diligence workstream, so each specialist sees their share.
Mark findings reviewed, flagged or dismissed as your team works through them.
Ask a question about a scored document, or get a summary, answered from its own text. Available for 30 days after the document is scored.
Compare two or more documents to catch figures, dates and parties that disagree, such as a CIM against the audited accounts. Comparisons are saved until you delete them.
Delivering
Each analysis produces a Risk Assessment Report: scores, findings, the verification plan and the evidence behind each finding.
How the platform works →Download a formatted report as PDF or DOCX to share or file.
Machine-readable output for your own tools, models and pipelines.
Download every report from a batch in a single file.
Every download is stamped with who downloaded it, their role and the time in their own timezone, so a copy filed in a data room identifies itself.
Across the deal
A deal room keeps a deal’s documents, people and results together. Growth includes 5 rooms, Pro 15 and Enterprise unlimited. Seats are unlimited on every plan.
Deal rooms → Clean rooms →See a room’s risk by category and workstream across every scored document, and how many documents have been scored. There is deliberately no single deal score, because an average hides the one category that matters.
Invite people as analysts or viewers. Viewers can read results but can’t upload.
Give the same person a different role per room: analyst in one, viewer in another, clean team in a third.
Team members accept a room’s confidentiality terms before they can open its documents or its risk summary.
The account owner can review each room’s own audit log of who did what, and when.
Ask Kai how to use the platform or how to read a report. Kai has no access to your documents.
For competitively sensitive material, kept in a separate database schema with its own key and room roles. The deal team sees nothing until a lead or counsel releases it, and every change, release decision and download goes into a hash-chained audit log. It’s software, not clean-team services.
From your systems
The REST API and the MCP server act as your account, not around it: same key, same plan limits, same role restrictions a person would hit.
API & MCP guide →Upload, screen, check status and download reports from your own systems, server to server.
Four screening tools for Claude, ChatGPT and other MCP clients: screen a document, fetch an analysis, submit a batch and check its status.
Pull scored results into your CRM or BI tools.
Risk by category across every room on the account, through the API.
Underneath everything
Every safeguard below applies to every plan, and the isolation is enforced in the database, not only in our code.
Security & compliance →Extracted text and findings are encrypted at rest under a key derived for your account alone.
The app limits every query to your account, and Postgres row-level security enforces it a second time.
Documents are processed by Anthropic’s Claude over encrypted TLS and are never used to train AI models.
Every upload, analysis, report view, download and change is recorded: who, what and when.
A scored document’s extracted text is deleted 30–31 days after analysis. Your reports stay.
Export your account’s data, or request its deletion, through the API.
Plan labels refer to the Growth, Pro and Enterprise subscriptions. The one-time per-deal plan and the Clean Rooms add-on are described on the pricing page.
Upload a filing or a contract and get a scored, source-checked risk report in minutes.
No credit card required