AI-assisted startup analysis
Analyze the startup, not just the submission.
OneSource turns founder answers and uploaded materials into an evidence-led due-diligence report. It structures the first pass, tests fit against the fund’s mandate, and gives reviewers clear assumptions to challenge before a decision.
Startup analysis
Illustrative report preview
Example company
NorthwindAI
AI infrastructure · Seed
Fund alignment
74/100
Evidence used
- Questionnaire
- Pitch deck
- Financial model
Analysis map
Evidence organized for review
Market opportunity
Sizing, timing, and segments
Product and traction
Evidence, milestones, and model
Team analysis
Experience, strengths, and gaps
Risk assessment
Severity, evidence, and mitigation
What the analysis covers
A structured view of the evidence—and the gaps.
Reports are designed to reduce first-pass synthesis work while keeping uncertainty and human review visible.
Multi-source synthesis
Read structured application answers together with PDF, DOCX, PPTX, XLSX, and text files, either separately or as one startup evidence packet.
Company and product
Extract the problem, solution, value proposition, product detail, technology context, company profile, and development stage supported by the source material.
Market and business model
Organize market sizing, timing, target segments, revenue model, pricing, acquisition approach, and available unit economics.
Traction and financials
Surface stated revenue, growth, customers, milestones, fundraising terms, use of funds, runway, and projections without padding missing fields.
Team and competition
Capture named team members and backgrounds, identify stated strengths and gaps, and map competitors, positioning, and potential moats.
Risk and scenarios
Structure risks by severity and mitigation, then separate supported downside, base, and upside assumptions when the evidence allows.
Fund-thesis alignment
For submitted deals, compare the company with the fund’s thesis, anti-thesis, preferred stage, industry, geography, check size, and scoring weights.
Reviewer feedback loop
Mark report assumptions confirmed, incorrect, or unclear; add corrections; and carry that guidance into future reports for the organization.
How the report earns depth
Traceable inputs, broad analysis, deliberate review.
The report is not a black-box verdict. OneSource records what evidence was available, structures each analytical lens, and leaves the final judgment with the investment team.
Inputs
Start from a live submission or upload a standalone diligence packet.
- Structured founder questionnaire responses
- Pitch decks and supporting PDFs
- Word documents, presentations, spreadsheets, and text files
- Multiple files analyzed independently or combined for one startup
Analysis
Create one navigable report instead of a pile of disconnected notes.
- Executive summary, problem and solution, product, and traction
- Market, business model, team, competition, and financials
- Risks with mitigations, SWOT, scenarios, and diligence questions
- Alignment score and breakdown when a fund mandate is configured
Human control
Treat AI output as a review surface, not an autonomous investment decision.
- Show whether questionnaire answers and documents were used
- Expose confidence, missing evidence, and validation warnings
- Confirm, correct, or clarify key assumptions
- Export a PDF or create a report share link when appropriate
From documents to diligence
A first pass your team can interrogate.
OneSource automates synthesis while preserving the checkpoints that make analysis trustworthy.
- 01
Collect the source packet
Use the submitted questionnaire and files, or upload one or more standalone documents for ad-hoc analysis.
- 02
Extract and organize evidence
Read the available text, tables, metrics, people, claims, and financial details across the complete packet.
- 03
Generate and validate the report
Build the structured analysis, calculate relevant alignment, and flag missing sections, inconsistent scenarios, or weak risk coverage.
- 04
Review, correct, and circulate
Challenge assumptions, retain reviewer guidance, then export or share the report as input to the fund’s decision process.
Give every startup a more rigorous first review.
Create a fund workspace to connect startup analysis with the pipeline and the decision record around it.