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Foundation AI Tech Stack
Document intake automation for legal and claims workflows
Foundation AI automates document classification and data extraction for law firms and claims departments using a production-heavy ML stack: transformers (BERT, RoBERTa), LLMs (GPT, Claude, Mistral, LLaMA), and classical models (XGBoost, LSTM). The engineering-skewed hiring mix and active project load around LLM fine-tuning and model optimization signal a shift from rule-based extraction toward learned models—a pattern typical of document-AI companies scaling accuracy across diverse document types and customer verticals.
Tech Stack 33 technologies
What Foundation AI Is Building
◆Challenges
- Manual document processing
- Seamless onboarding of new customers
- Process improvements in automation testing
- Integration into case management systems
- Automating repetitive tasks
- Inefficient case file management
- Reducing costs
- Improving accuracy
- Enhancing efficiency
- Successful implementation of our product
▲Active Projects
- Extract filer implementation
- Implementation of foundation ai platform
- Go-live and hypercare support
- Customer onboarding
- Llm fine-tuning for classification and extraction
- Model optimization with quantization and pruning
- Deploying nlp models in production
- Hypercare and adoption optimization
- Go-live readiness and stabilization
Hiring Activity
Steady15 roles · 5 in 30d
Department
Seniority
Company intelligence
