Atlas Agents: Autonomous Execution on Your Firm's Knowledge Graph

What Are Atlas Agents?

Atlas Agents are autonomous executors that live on Singularity v6, AtlasAI's curated knowledge graph platform. Unlike stateless AI assistants, Atlas Agents have a persistent view of your firm's data: iManage, SharePoint, OneDrive, NetDocuments, email. They read, classify, link, and refine this data continuously. When you ask an agent to execute a workflow, it operates against a graph shaped by months of agentic curation, so every decision is grounded in your actual precedents, deals, and case work.

Two Execution Contexts

Atlas Agents work in two places. Inside Workspaces (matter-scoped environments), agents handle document review at scale: upload hundreds of documents, agents classify and route them, execute pre-review (privilege, conflicts, scope), run substantive review (clauses, R&Ws, indemnification, diligence findings as tabular reviews), then draft new client documents from the output. Post-review, agents automatically generate SPAs, NDAs, indemnification schedules, diligence memos, and closing checklists back into the workspace. Outside Workspaces, agents curate the knowledge graph itself. As new iManage, SharePoint, or Drive content lands, agents read it, classify it by practice area and matter, link it to existing documents and clauses, and refine it so downstream retrieval and drafting see fresh, accurate, connected context.

Auditable, Multi-Step Execution

This month we shipped agent task boards so every action in a workflow is visible and auditable. When an agent executes a task, you see which documents it processed, what it extracted, which clauses it flagged, and exactly which new documents it generated. Multi-step execution now honors task references, so agents can chain actions: extract privilege logs, compare to firm precedent, generate redlines, then draft a privilege memo, all in one logical flow. The planner layer dispatches workflows based on user intent ("review all purchase agreements for indemnification clauses"), breaks them into steps, executes them in parallel where safe, and writes findings back to the workspace.

Concrete Example: M&A Deal Review

An AmLaw firm's M&A team runs a Deal Review agent on every new transaction. The agent:

1. Classifies 300 uploaded documents (SPA, exhibits, schedules, board minutes, cap table, diligence reports). 2. Extracts key representations, warranties, and indemnification obligations as tabular reviews. 3. Compares findings to 5 years of firm deal precedent stored in the curated graph. 4. Flags missing reps, unusual carve-outs, and deviations from firm standard. 5. Drafts an indemnification schedule from the output, a compare-and-contrast memo against prior deals, and a closing checklist.

All output lands back in the Workspace. The team reviews it in hours, not days. The agent's task board shows exactly which documents it read and what it found. Next quarter, when a new deal comes in, the agent runs the same workflow again, benefiting from the updated knowledge graph.

Grounded in Your Data

The difference between Atlas Agents and a generic AI assistant is grounding. Your M&A agent doesn't reason about generic deal structure. It reads your actual precedent agreements from iManage, your practice area guidance from SharePoint, your matter email threads. The curated graph continuously refines this context as new deals close. So your agent's indemnification analysis is shaped by what your firm actually does, not what an LLM thinks M&A looks like. This makes the output both faster and more trustworthy.

How to Try It

Agents are live in Singularity v6. Inside Workspaces, create a new matter, upload documents, and stage them. The agent interface will appear on the task board. Define a workflow ("extract privilege logs, then draft a privilege memo") or pick from practice-area workflows your team has already built. The agent will execute and write findings and new documents back into the workspace. Outside Workspaces, agents run continuously on your configured data sources (iManage, SharePoint, OneDrive) and curate the knowledge graph. See it live at https://atlas-ai.io.