Simulated Data to Power Enterprise AI Adoption
Testing and training AI requires realistic data. Using real customer data creates privacy and security risk. Seedless solves this. We generate highly realistic simulated data (emails, contracts, health records, financial documents, and more) so your AI performs in the real world without exposing real people.
Consilio - Seedless strategic partner for legal AI innovation
Prosearch - Seedless strategic partner for AI innovation
Definely - Seedless strategic partner for AI innovation
Boehringer Ingelheim - Seedless strategic partner for AI innovation
Latham & Watkins - Seedless strategic partner for legal AI innovation
Consilio - Seedless strategic partner for legal AI innovation
Prosearch - Seedless strategic partner for AI innovation
Definely - Seedless strategic partner for AI innovation
Boehringer Ingelheim - Seedless strategic partner for AI innovation
Latham & Watkins - Seedless strategic partner for legal AI innovation
The Problem
How to Fix It
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Data Scarcity is the Biggest Roadblock to Corporate Adoption of AI
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Buying or building enterprise AI tools requires access to high quality business data for testing and training
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Privacy regulations and data security concerns prevent companies from using their own data to test or train new tools.
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The resulting scarcity of available data is the blocker to widespread adoption of AI for business; no testing means no trust.
Seedless Generates Simulated Data to Enable You to Safely Embrace AI
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Simulated data is secure, privacy-compliant and isn't seeded with your actual corporate data
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Incorporates realistic business scenarios to test and train AI on nuanced edge cases
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Includes answer keys to benchmark performance and validate training results
See How Simulated Data Works
Creating Business Data That's Fit for Purpose
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Narrative Arcs
Our approach uses agent-based role playing and world-building, resulting in diverse, contextually grounded content across communications, documents, records, and reports
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Realistic Scenarios
Our data reflects real business situations including edge cases and exceptions that matter most when evaluating AI accuracy and reliability
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Optimized for Quality
Our patent-pending process uses multiple AI models working together to produce data that is highly realistic and statistically valid, not just plausible-sounding, but rigorously calibrated
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Custom-Built
Every dataset is built to spec and includes 'answer keys' (ground truth annotations) so you can benchmark your AI's performance against a known standard
Key Industries Based on Our Domain Expertise
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Banking & Financial Services
Data to test tools for fraud detection, AML compliance, regulatory stress testing, litigation and investigations.
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Life Sciences & Healthcare
Patient health data for clinical trials, drug development tools, regulatory filing systems, marketing tools and healthcare communications.
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Legaltech
Data for testing eDiscovery, contract analysis, legal research AI, and document review tools—without accessing client data or privileged communications.
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Law Firms
Data to test and train tools for identifying relevance and privilege, fact-finding in investigations and litigation, and contract lifecycle management.
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