Build specialized models for your legal team or practice
Large language models can be leveraged effectively in the legal sector, offering significant advantages in terms of efficiency, accuracy, and cost-effectiveness. Read on to find out how Arcee’s end-to-end SLM adaptation system can help you build your own model across your legal function.
Discover potential legal-related uses cases and their benefits
Regulatory Compliance
Arcee’s SLM Adaptation System can build models that monitor and ensure compliance with various laws and regulations.
Due Diligence
Automate due diligence processes by identifying key issues and risks in transactions through scanning of legal documents at scale.
E-Discovery
Use your AI to sift through large amounts of electronic data to identify and extract relevant information for litigation.
Predictive Analysis
Use Arcee’s SLM Adaptation System to build AIs that analyze past cases to predict potential outcomes of current cases.
Legal Writing
Build SLMs to generate drafts of legal documents, memos, and contracts based on your past work and other relevant data.
Contract Review and Analysis
Your Arcee-powered AI can be trained to review and analyze contracts, identify key terms, clauses and potential risks.
Train, deploy, and continuously maintain your AI for any use case
Thanks to the domain adaptability of our product, you can efficiently train and deploy your own SLMs across a plethora of use cases, whether it is for internal tooling, or for your customers.
Healthcare
Learn how Arcee's end-to-end adaptation system can help you build specialized LLMs for healthcare.
Finance
Learn how Arcee's end-to-end adaptation system can help you build specialized LLMs for finance.
Legal
Learn how Arcee's end-to-end adaptation system can help you build your own language models across your legal function.
Insurance
Learn how Arcee's end-to-end adaptation system can help you build specialized LLMs for insurance.
Start building your SLMs today
Book a call with our team to discuss how Arcee can help you train, deploy, maintain, and continuously improve your smaller, secure, specialized, and scalable language models.