Harvey's AI agents tackle full legal workflows

The most exhausting part of legal practice isn't always arguing in court. It is usually the hundreds of hours spent digging through discovery documents, depositions, and emails just to turn them into memos and presentations.

Legal AI startup Harvey is now aiming to take over that entire background pipeline. The company just rolled out Agents, autonomous AI bots built to execute end-to-end legal workflows rather than just answering one-off chat prompts.

According to the company, these agents can handle complex assignments across 13 legal domains, taking on everything from case research and contract drafting to memos and client-ready slide decks.

Splitting big legal tasks across parallel bots

The central idea here is parallel execution. Instead of bogging down a single model, Harvey coordinates a team of agents that break large legal projects into smaller pieces, work in the background simultaneously, and deliver review-ready outputs.

It handles a wide range of formats as well. Teams can feed agents mixed inputs including text documents, images, audio recordings, or video, and receive structured reports, presentation decks, or interactive pages depending on what the assignment calls for.

There is also a scheduling feature. Law firms can set recurring agents to monitor shifting regulatory policies, run periodic compliance reviews, or refresh case summaries automatically before attorneys sit down at their desks.

Harvey claims the platform already runs over 700,000 tasks daily using agents, extracts 50 million terms every week, and analyzes more than 5.8 million documents each day.

Baking internal playbooks into custom agents

For legal professionals, the biggest hurdle with generic AI is getting it to follow firm-specific standards. Harvey introduced Agent Builder, which lets teams embed their internal knowledge bases, precedent language, and playbooks directly into custom agents without repeatedly typing out system prompts.

Through native connectors, these agents also plug securely into Microsoft tools and traditional document management systems (DMS) to pull precedents and files directly from existing firm archives.

Crucially, Harvey emphasizes keeping humans in the loop under the mantra of delegating the work while owning the judgment. Attorneys can inspect and adjust the execution plan before an agent starts, and the system uses proactive nudges to bring attorneys in whenever human judgment is required. Every claim includes verifiable source citations, and all execution steps are logged for compliance audits.

Why it matters

This marks a clear shift in professional generative AI from simple chatbots to autonomous digital associates. Instead of asking AI to summarize a single memo, firms are starting to hand off the entire multi-day research and formatting workflow.

Harvey's smartest choice is avoiding any talk of fully automated lawyering. By building in strict citation audits, review checkpoints, and DMS integrations, it addresses the exact control and liability fears that keep law firms from deploying AI on critical matters.

That said, this is strictly an enterprise-grade play designed for big law and corporate legal departments. The system requires requesting a formal demo to access, and the integration effort will likely keep smaller practices on the sidelines for now. But for firms with high billable pressure, parallel legal agents could quickly shift from a neat tech experiment into an operational necessity.