How Atlas Agents Execute Legal Work End-to-End

The Execution Layer

AtlasAI Singularity (v6) builds on a curated knowledge graph: the firm's documents from iManage, SharePoint, OneDrive, NetDocuments, and email are continuously ingested and refined by agents so that every Atlas response is grounded in real precedent, not generic training data. Atlas Agents are the execution layer that makes that graph actionable.

Agents do two jobs. Inside Workspaces, they execute matter workflows: reviewing documents at scale, designing and running pre-review processes (privilege screening, conflict detection, scope validation), executing substantive review against the firm's curated precedent, and generating new client documents from the findings. Outside Workspaces, they curate the knowledge graph itself, reading and classifying new content as it lands from the firm's document systems so the graph stays current and sharp.

What Shipped This Week

We launched agent task boards that show real-time execution state, allowing teams to watch agents work through review queues and intervene if needed. The planner layer now dispatches automatically from chat prompts into multi-step workflows without requiring manual JSON formatting. We also shipped agent-generated folder structures that organize documents as they flow through pre-review, substantive review, and post-review stages, so the workspace folder rail reflects the actual work stages of the matter.

These changes were grounded in hardening the execution layer: we expanded the token budget for the planner on large matters, added recovery logic for JSON parsing failures, and added defensive serialization on the task board to prevent malformed data from crashing the UI.

How It Works in Practice

Consider a corporate M&A team handling a deal with 200+ SPA exhibits and schedules. The workflow looks like this:

Upload and classification. The team stages the documents in a Workspace. Atlas agents immediately begin reading them, classifying by document type (exhibit, schedule, certificate), flagging privilege, detecting conflicts against the firm's matter list from the curated graph.

Pre-review processes. Before substantive review starts, agents run scope validation (is this document in scope?), privilege screening (is this covered by attorney-client privilege or work product?), and firm precedent matching. For each clause or schedule item, agents compare it against the firm's deal precedent from the curated graph and flag deviations.

Substantive review and extraction. Agents execute the practice-area playbook: extract key commercial terms (purchase price, reps and warranties, indemnification caps, survival periods), mark problematic language, roll up findings into a structured tabular review. The tabular review is the human interface; the actual work happens agentically.

Document generation. From the extracted findings and the firm's template library (also part of the curated graph), agents draft marked-up SPAs showing proposed changes, generate an indemnification schedule rollup, and produce a closing checklist. All new documents are written back into the workspace and ready for human review.

The entire workflow runs on documents that have been staged and routed by agents. The human team reviews the tabular findings, approves or adjusts agent-drafted documents, and moves to the next stage. What used to take 2-3 weeks of manual document assembly and precedent hunting now takes days.

Beyond Workspaces: Graph Curation

Outside matter-scoped work, Atlas Agents continuously curate the firm's knowledge graph. As new files land in iManage or SharePoint, agents read them, classify them by document type (precedent SPA, term sheet, engagement letter, work samples), extract key metadata (parties, deal size, completion date), and link them to related documents already in the graph. This means the firm's precedent library stays organized and discoverable without manual curation. When a new matter starts, the curated graph has already surfaced the most relevant prior deals.

Concrete Stages in the Codebase

We shipped agent-generated folder hierarchies this week so that the workspace folder rail reflects real work stages. Agents now emit structured folder creation and document move commands, so documents flow from "Uploaded" to "Pre-Review" to "Reviewed" to "Draft Output" as they move through the agent workflow. We also hardened the planner's JSON parsing to recover gracefully from malformed responses on high-complexity matters, and added a defensive serializer on the agent task board to prevent unterminated strings from crashing the board render.

Who Uses This

Corporate teams use agents for M&A document review, deal diligence, and closing document assembly. Litigation teams use agents to run privilege reviews across thousands of matter files. IP teams use agents to execute patent diligence playbooks, extracting claims language and comparing to prior art from the curated graph. Real estate teams use agents to produce lease abstracts and tenant requirement checklists. Commercial teams use agents to run NDA precedent analysis and redline generation.

The common pattern: stage documents once, agents execute the firm's playbook against the curated knowledge graph, new client documents emerge.

Getting Started

If your team is running high-volume document review, diligence protocols, or closing workflows, agents can cut execution time dramatically. Visit https://atlas-ai.io to see task boards, the workspace folder structure, and agent-drafted output in action.