Volume before judgment
Most of the first two weeks go into reading and reconciling. The questions that decide the deal come last, when there is the least time for them.
Needl.ai reads every document in the room, validates the model against the source data, benchmarks the financials and flags what matters. A first pass in around 30 minutes, a fully cited investment committee memo in hours, and every finding traced back to the page it came from.
A data room lands with a few hundred files and a committee date. Contracts, models, decks and disclosures get read one at a time, numbers get rebuilt in spreadsheets, and the clause that changes the thesis turns up late, if it turns up at all.
Most of the first two weeks go into reading and reconciling. The questions that decide the deal come last, when there is the least time for them.
The CIM, the model and the filings rarely tell the same story. A projection the underlying data cannot support is easy to miss when the checks are manual.
Risks live in emails, notes and slides. When the committee asks where a finding came from, someone goes back to the room to look.
The same room, read by Needl.ai, comes back as a first pass, a validated model, a consolidated risk view and a memo, in that order.
A go / no-go checklist and the risk flags that matter, around 30 minutes after the room is loaded.
Projections checked against the underlying data, with every mismatch surfaced before the IC discussion.
Commercial drivers, partnership dependencies, legal and covenant exposure and IP risk, consolidated and ranked by severity.
Thesis, risks, financial validation and recommendation in your format, with each conclusion linked to its evidence.
How a deal moves through Needl.ai, start to finish.

Upload the files or connect the drive the room lives in. Contracts, financial models, partnership agreements, employee documents and investor decks are read, classified and indexed, and a connected view of the deal is ready in minutes.
You getA readiness view of every file in the room.

In around 30 minutes Needl.ai returns a first-pass diligence assessment: a go / no-go checklist across the business and the flags that decide whether the deal deserves the full workflow.
You getA go / no-go checklist and the key risk flags.

The financial model is checked against the underlying data. Inconsistencies are caught here, like a projected $20M in revenue against a realistic $2M.
You getA validated model with every mismatch flagged.

Commercial drivers, partnership dependencies, legal and covenant exposure and IP risks are reviewed automatically and consolidated into one ranked view, each with its observed evidence and a recommended action.
You getA consolidated risk and red-flag report.

A fully cited investment committee memo, with thesis, risks, financial validation and recommendation, in your preferred format. Analysts dig deeper with follow-up questions and trace every conclusion back to the supporting evidence.
You getA cited IC memo, exported as a document.
The workspace is organised the way a deal team works: one page per question, and a source on every figure.
Upload or connect the room. Files are classified, parsed and indexed, and you can see what has been read before anything runs.
The business, its ownership and its capital structure, summarised from the documents with sources.
Revenue composition, trends, concentration and margin, charted from the room and labelled with the page each number came from.
Projections checked against the underlying data. Mismatches are flagged with the figures side by side.
Critical and high findings with the observed evidence, the condition, the analysis and a recommended action. Linked flags form a risk chain.
Contract review with the clauses that matter, and covenant health: leverage, coverage and headroom, with what-if scenarios.
Preliminary risk assessment and consolidated risk reports, ready to circulate before the full memo lands.
The comprehensive due diligence memo, in your structure. Export it as a document or share a link with the deal team.
Every figure carries a View source link. Follow-up questions are answered from the room, with citations you can open.
“81 files became a connected view in minutes. A first-pass assessment landed in 24 minutes, and the platform caught a ~$20M revenue projection against a realistic ~$2M, plus $60-75K in external advisory and legal costs avoided.”
“Leverage, interest coverage, free cash flow, asset coverage, and covenant health surfaced in a single view, with what-if scenarios and a cited IC memo in under 30 minutes.”
Needl.ai runs in your own AWS or Azure account, or fully on premise. Your keys, your permissions and your egress rules apply, and no document leaves your perimeter.
AICPA SOC 2
ISO 27001 certified
ISO 42001 in progress
GDPR compliant
CASA assessedWhat deal teams ask before running live diligence on Needl.ai.
Most teams get a first-pass assessment around 30 minutes after loading the data room, including a go / no-go checklist and key risk flags.
Needl.ai checks projections against the underlying model and source data, then highlights mismatches so analysts can verify assumptions before the IC discussion.
Yes. It compiles a fully cited IC memo with thesis, risks, validation findings and recommendations in your preferred structure, and exports it as a document you can circulate.
Yes. Every conclusion is traceable to the underlying document evidence, so follow-up questions can be answered quickly and transparently.
Full data rooms: contracts, financial models and projections, partnership and legal agreements, investor materials and disclosures. Upload the files or connect the drive the room lives in.
In your own AWS or Azure account, or fully on premise. Your keys, your permissions and your egress rules apply, and no document leaves your perimeter.
Every figure and conclusion carries a View source link to the page it came from, so a reviewer opens the evidence instead of trusting the model.
On your own data, in your environment. Bring a live deal or a closed one and watch the first pass, the model validation and the memo come back.