Self-Hosted Legal AI Software Inside Your Firm's Tenant

Contract review for incoming paper: clause extraction, market-terms comparison, anomaly detection against the firm's playbook and disclosure-schedule reconciliation. Contract drafting for outgoing paper: first drafts, clause-library suggestions, redlines and matter-type templates. Legal research across the firm's prior work product, internal memos and matter document sets. It also summarizes depositions and answers questions over the firm's full matter corpus. We build custom workflows for specific practice areas too, such as M&A diligence, personal injury medical chronologies and demand letters.

It gives the firm a simple, documented data path. With self-hosted embeddings and a self-hosted model, matter content stays inside the firm's tenant and is processed only on systems the firm controls. The firm's ethics and risk team can use that as the basis for its ABA Formal Opinion 512 risk evaluation, OCG AI-use disclosures, NDA AI clauses and the guidance of its state bar, the SRA, the Federation of Law Societies of Canada or the Law Council of Australia. The compliance decision stays with the firm's counsel, and we supply the architecture and audit documentation they need.

Harvey AI and Hebbia quote each firm through their sales teams, so a fair comparison starts from the quote your firm receives. A private deployment is a one-time build plus hosting (GPUs or cloud compute) and an optional flat managed retainer, so the cost stays steady as the firm adds lawyers. The firm also gets review, drafting, research and matter chat in one calibrated deployment. A strategy session puts the two side by side for your firm's headcount and workload.

Yes to both. We deploy into the firm's existing AWS, Azure or on-premise environment, or into a firm-controlled tenant we provision in the region the firm prefers, such as Toronto, London or Sydney. For air-gapped or regulated work, we pair the pipeline with self-hosted embedding models and self-hosted LLM serving (vLLM, SGLang or Ollama on GPUs inside the perimeter), and the full data path runs on the isolated network.

Our target is 4–6 weeks from kickoff to lawyers running workflows in production. Weeks 1–2 cover tenant deployment, SSO and audit logging. Weeks 2–3 cover corpus ingestion (engagement letters, NDAs, M&A agreements, employment, commercial and licensing documents). Weeks 3–4 cover retrieval tuning and playbook calibration to the firm's market positions, and from week 4 lawyers run review and drafting workflows. We confirm the schedule once we have seen the firm's corpus. The managed engagement covers ongoing operation (model updates, connector additions, version upgrades and quarterly playbook reviews). The firm's IT team authorizes the tenant on day one and confirms audit-log retention, and we handle everything in between.