Bright Run

Bright Run offers a private AI platform that lets small and mid‑size knowledge‑focused businesses securely ingest proprietary documents and automatically generate training data to fine‑tune open‑source models.

Updated 2 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Small and mid‑size knowledge‑focused businesses lack affordable tools to apply AI to their proprietary documents, SOPs, and expertise without exposing sensitive information. Existing public AI services require uploading data to shared models, risking confidentiality, compliance breaches, and loss of competitive advantage.

Solution

Bright Run provides a private AI platform that lets businesses securely ingest their proprietary documents (PDF, DOCX, TXT, Markdown) and automatically generate semantically diverse training data. The system fine‑tunes open‑source foundation models using LoRA adapters within a SOC‑compliant AWS Bedrock environment, ensuring the model runs on dedicated inference endpoints isolated from other tenants. Users can query the resulting model through a secure, branded chat interface or via retrieval‑augmented generation that answers directly from the uploaded knowledge base. The end‑to‑end pipeline requires no machine‑learning engineering expertise, delivering a custom AI assistant in hours while maintaining full data ownership and compliance with standards such as SOC 2, ISO 27001, GDPR, and HIPAA eligibility.

Target Audience

Primary customers are small to mid‑size knowledge businesses—consulting firms, legal practices, financial advisory groups, and other organizations that rely on proprietary expertise and need secure, in‑house AI assistance for their teams.

Features

Drag‑and‑drop upload of PDFs, DOCX, TXT, and Markdown with automatic text extraction, chunking, and embedding generation
AI‑powered creation of thousands of diverse training conversation pairs from proprietary content
One‑click LoRA fine‑tuning pipeline that customizes foundation models without full model retraining
Retrieval‑augmented generation (RAG) for accurate, source‑cited answers grounded in the uploaded knowledge
Private deployment on dedicated AWS Bedrock inference endpoints with SOC‑2 Type II, ISO 27001, GDPR, and HIPAA‑eligible compliance
Secure employee chat interface that keeps all queries and responses within the organization’s security boundary
Analytics dashboard with A/B model evaluation, usage metrics, and prompt improvement tools