Create your member account
Enter your name, company and work email. DOT3METRICS uses email-code access instead of a password.
FIRST VENTURE GUIDE
How to use DOT3METRICS.
Build the venture profile through a guided AI interview, attach evidence, review normalized data, then run the assessment and reputation engines.
FIRST RUN
Your first venture in six steps.
Verify your email
Enter the six-digit verification code and open the member workspace.
Create a venture
Choose New Venture. This creates the persistent workspace where profile data, assessments, evidence and reputation history are stored.
Complete the AI interview
The AI asks one question at a time about the company, product, team, traction, capital, financials, token model and operating evidence. Your answers populate the structured venture profile automatically.
Review evidence and gaps
Before scoring, check the normalized profile, missing fields, unsupported claims and evidence strength. You can correct the profile before assessment.
Run the assessment
Deterministic algorithms calculate venture, risk and reputation signals. The LLM then explains the result, flags contradictions and recommends the next evidence or action.
WHAT THE AI BUILDS
The profile is created behind the conversation.
You do not need to understand the internal schema. The interview converts answers into a structured operating profile.
Name, sector, jurisdiction, lifecycle and market.
Product status, technical scope, deployment and evidence.
Funding target, capital raised, burn, runway and use of funds.
Founders, roles, experience and operating coverage.
Supply, vesting, reserves, liquidity and governance structure.
Documents, reported facts, corroboration, confidence and gaps.
FAQ
Frequently asked questions.
You can begin with only the basic company idea. For a stronger assessment, have the pitch or white paper, team information, funding target, product status, financial assumptions, token details if applicable, and any evidence supporting traction or milestones.
No. The intended intake is conversational. The AI asks focused questions and fills the structured venture profile in the background.
Yes. The venture profile remains editable. Updated information should trigger refreshed readiness, evidence and assessment results rather than creating a separate disconnected profile.
The LLM interviews the member, extracts and normalizes information, classifies evidence, identifies gaps and contradictions, and explains assessment results.
No. Core scores should come from deterministic algorithms using normalized profile data. The LLM interprets and explains the evidence and results.
Evidence strength reflects how well important venture claims are supported. A self-reported statement is weaker than a document-supported, externally corroborated, machine-verified or independently audited claim.
Reputation is a longitudinal signal built from behavior and outcomes such as milestone delivery, reporting consistency, financial discipline, governance participation and verified execution history.
Yes. New evidence or corrected profile data can be normalized and reassessed so the stored venture history shows how the venture changes over time.
The workspace can track milestones, risk, liquidity, governance, evidence gaps and reputation over time. The assessment becomes the baseline rather than a one-time report.
Yes. Use the interactive demo to review the operating experience with mock data before creating a member account.
READY
Build your first venture profile.
Start with the guided member flow or inspect the mock-data demo first.