Law.
AI built for work that deserves a second opinion. Research, analyze, draft, and review complex legal work using coordinated frontier AI models - with the attorney retaining control over the final legal judgment.
One model that both writes and checks its own work is a structural weakness.
A single matter often requires several forms of reasoning at once - issue identification, source analysis, factual organization, interpretation, drafting, counterargument development, citation verification, and final review. A single model can attempt all of those tasks, but the same system being responsible for both generating the work and evaluating it is a structural weakness.
Omnesly takes a different approach. You define the objective. Omnesly decomposes the request into the right sub-tasks, coordinates frontier models across them, and lets an independent model challenge assumptions and inspect prior work before anything is synthesized into a result. The value isn't autonomous legal judgment - it's more rigorous AI-assisted preparation for your own review.
An AI legal team, not a single model.
A conventional multi-model interface still leaves you responsible for opening several models, transferring context, repeating the prompt, comparing answers, resolving contradictions, and assembling a final response. MOSAIC is the layer that handles that coordination.
| Role | Responsibility | Why it adds value |
|---|---|---|
| Issue analyst | Extracts the legal questions, required elements, and factual dependencies, and drafts a research plan. | Prevents the workflow from jumping directly to a conclusion. |
| Authority analyst | Analyzes supplied or verified sources and maps propositions to the relevant authority. | Separates source analysis from final drafting. |
| Adversarial reviewer | Builds the strongest opposing interpretation and identifies unfavorable facts or missing support. | Introduces a deliberately independent challenge. |
| Verification reviewer | Checks whether the draft accurately reflects the materials available and flags unsupported statements. | Reduces the risk of polished but insufficiently supported reasoning. |
| Synthesis model | Reconciles the analyses and organizes the result into one coherent, attorney-facing work product. | Produces one usable output rather than a pile of model responses. |
Where legal teams use Omnesly.
| Workflow | How Omnesly can assist | Illustrative output |
|---|---|---|
| Legal research | Frame issues, summarize authorities from your own research tools, compare interpretations, surface contrary arguments, and prepare a research structure. | Research memorandum, issue map, authority table |
| Litigation | Organize pleadings, exhibits, testimony, correspondence, and discovery; build chronologies; compare factual assertions; identify inconsistencies and test arguments. | Chronology, witness matrix, argument map, deposition prep |
| Contracts | Extract obligations, compare clauses, identify unusual or high-risk language, evaluate commercial impact, propose revisions and redlines. | Issues list, clause matrix, negotiation brief, contract summary |
| Due diligence | Review large sets of transaction documents, classify provisions, surface consent/change-of-control/termination issues, and prioritize attorney review. | Diligence matrix, red-flag report, open-items tracker |
| Regulatory & compliance | Compare requirements against policies or procedures, summarize changes, identify gaps, and translate complex requirements for internal teams. | Policy gap analysis, compliance checklist, management memo |
| Legal drafting | Turn approved analysis into structured first drafts while preserving the attorney's ability to review, revise, and control final language. | Memorandum, client letter, internal brief, presentation |
From analysis to a finished work product.
Research and reasoning stay connected to the document, matrix, or deck you actually need to deliver - not a separate copy-paste step.
Legal memorandum
Research and reasoning are organized into Issue, Brief Answer, Facts, Analysis, Counterarguments, Open Questions, and Conclusion. You can edit the document directly.
Diligence matrix
Extracted provisions become a structured table with document name, clause, issue, risk level, follow-up question, and responsible reviewer.
Client presentation
Approved findings can be translated into a concise presentation for executives or a client team without rebuilding the analysis from scratch.
One request, five perspectives.
"Analyze whether this provision is likely enforceable under the supplied authorities, identify the strongest counterarguments, flag facts that could change the conclusion, and prepare an attorney-facing memorandum."
- Deliverable
- A synthesized legal memorandum in Issue / Brief Answer / Facts / Analysis / Counterarguments / Open Questions / Conclusion format, with each section traceable back to the model role that produced it.
- Independent review
- The adversarial and verification models run before synthesis - not after - so the first draft the attorney sees already reflects a challenged, cross-checked analysis.
Security & control.
Local-first by default
Matter files and conversation history are stored on your device. Nothing is uploaded unless you turn on optional sync.
Direct to the provider
Requests go straight from your device to the provider's own API. Omnesly never sits in the middle as a proxy.
No training on your data
We don't use your prompts or responses to train any model. What you send is governed by that provider's own policy.
Encrypted at rest
API keys are stored using your OS's secure credential storage - Keychain, Credential Manager, or Secret Service - never as plain text.