AI for legal

AI for legal teams, with a lawyer signing off

OceanLab builds AI into contract, policy and discovery work. The AI extracts, compares and cites; a lawyer decides every flag and signs off. Every example below is a product we built.

AI product builds

Builds in this industry

Countries

Frameworks cited

Proof

OceanLab product builds

AI products we designed and built in this industry. Each one is a full case study with screens, scope and the rules it was built for.

LegalTech·🇿🇲Zambia

Mukwa - AI Contract Review Checked Against the Playbook and Signed Off by a Lawyer

Designed and built a clickable contract review tool for the in-house legal team of a Lusaka copper miner: the AI extracts each clause of a third-party contract, compares it with the company playbook, flags risks with a plain explanation and drafts redlines, while a lawyer decides every flag and only a lawyer with the right authority can sign off.

AIEnterprise

LegalTech·🇪🇨Ecuador

Brújula - AI Policy Assistant That Cites the Clause and Escalates the Risky Questions

Designed and built a clickable internal policy assistant for a Guayaquil shrimp farmer, processor and exporter: staff ask in Spanish or English and get answers built only from company policies, each statement linked to its clause and version, while gift approvals, conflicts and possible breaches go to Compliance, HR or the confidential Speak Up channel instead of being answered.

AIEnterprise

LegalTech·🇺🇸United States

Chaffline - E-Discovery Search and Document Review Platform

Designed and built a clickable e-discovery platform for a Chicago litigation support firm that hosts and reviews data for US law firms: a dashboard across every matter, each matter's path from collection to production, Boolean, proximity and concept search, and a review pane where contract reviewers code documents with the privilege basis recorded at the moment of the call.

EnterpriseAI

LegalTech·🇷🇴Romania

Hotar - Sell-Side Contract Lifecycle Management with an Approval Matrix

Designed and built a clickable contract lifecycle system for a Cluj-Napoca software company selling to EU and US customers: contract requests from CRM deals, a board of every contract in negotiation, a contract workspace with versions, clauses and signature level, and approvals routed by a fixed matrix of discount, liability, payment and data protection rules.

EnterpriseAI

Use cases

Where AI earns its place

Each use case names the builds that did it.

Contract review

The AI extracts each clause of a third-party contract, compares it with the company playbook, flags risks in plain words and drafts redlines, while a lawyer decides every flag.

Mukwa - AI contract review

Policy answers that cite the clause

Staff ask in their own language and get answers built only from company policies, each statement linked to its clause and version. Risky questions go to Compliance or HR instead of being answered.

Brújula - AI policy assistant

E-discovery search and review

One dashboard across every matter, Boolean, proximity and concept search, and a review pane that records the privilege basis at the moment of the call.

Chaffline - E-discovery search

Contract lifecycle

Contract requests straight from CRM deals, a board of every contract in negotiation, and approvals routed by a fixed matrix of discount, liability, payment and data protection rules.

Hotar - Contract lifecycle management

Compliance

What to plan for

The rules that shape AI in this industry. General information, not legal advice: check with your own counsel.

The lawyer stays responsible

Professional conduct rules keep the lawyer accountable for advice and filings, whatever tool drafted them. Build sign-off into the flow, with only the right people able to approve.

Privilege and confidentiality

Record privilege calls as they are made, keep client data inside the firm's own systems, and control which model sees what.

Answers from your own sources

Legal answers should come only from the documents you trust, with every statement linked to its source, and a plain "I don't know" when the sources are weak.

EU AI Act

AI that helps a judicial authority research and interpret facts and the law, and apply the law, is on the EU AI Act's high-risk list (Annex III). Check where your use case falls.

Signatures and data transfers

Contract tools have to meet e-signature law, such as eIDAS in the EU and ESIGN and UETA in the US, and data transfer rules when contracts cross borders.

Data protection

Discovery and contract data is full of personal data, so GDPR, CCPA and similar laws apply to how it is stored, searched and shared.

Frameworks our AI builds here cite

CCPA · 2GDPR · 1HIPAA · 1eIDAS · 1

How it works

From one workflow to production

01
Pick the workflow
We start from one workflow your team wants off its plate and agree what a working result looks like.
02
Clickable AI prototype
Your team tries the flow on a clickable prototype before any production code is written.
03
Production build
We build the production version, with the approval steps and records your industry needs.
04
Launch and improve
It goes live in your team's hands, and we tune it as real work runs through it.

Priced either way, whichever suits the work: outcome-based, paid per milestone, or hourly at $30-50 depending on role and seniority. More on AI automation →

FAQ

Questions teams ask

What can AI do for a legal team?

Take first-pass reading off lawyers: extract and compare contract clauses against a playbook, answer staff policy questions with the clause cited, search and review discovery data, and route contract approvals by rule. Each of these is a product OceanLab built.

Does a lawyer still sign off?

Yes. In our contract review build the AI flags and drafts redlines, a lawyer decides every flag, and only a lawyer with the right authority can sign off.

Can the AI make things up?

Our policy assistant answers only from the company's own policies and links every statement to its clause and version, so a reviewer can check each one. Questions that carry risk go to a person instead of being answered.

How is it priced?

Either way, whichever suits the work: outcome-based, where you pay per milestone, or hourly at $30-50 depending on role and seniority.

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Are you an AI lab looking for human training or evaluation data? That is a separate offer, OceanLab Labs.

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