Governed AI for legal teams

AI you can trust with every contract

Turn your existing contracts into governed AI agents in 24 hours. They handle the lifecycle end-to-end, acting on your data, following your rules, and scoring every decision.

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Draft

negotiate

sign

Store

renew

amend

terminate

archive

destruct

No more babysitting legal AI

Most legal AI looks helpful, until its decisions force you to proof-read all outcomes. Avo makes every action explainable, verified, and accountable so you don't have to babysit AI anymore.

Superficial automations

One-off drafting or review tools. No context. No governance. High risk.

Unreliable by design

Outputs change with every user or prompt. No consistency. No accountability.

Black-box workflows

Outputs change without context or reasoning. You never know why.

Decision systems

Agents that reason, verify, and act within rules. End-to-end intelligence, not isolated steps.

Governed agents

Each agent is built from your playbooks and organizational knowledge

Transparent logic

Every AI decision explained, verified, and stored through the 5D Engine™ and Scorecard.

Want this for your company?

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How Avo makes it happen

Instant setup

Connect Drive, Box, or SharePoint in minutes.

Auto-mapping

Avo detects and structures contracts automatically.

Zero migration

Start working with what you already have.

Avo storage integrations

Instant setup

Connect Drive, Box, or SharePoint in minutes.

Auto-mapping

Avo detects and structures contracts automatically.

Zero migration

Start working with what you already have.

Avo 5D engine model

Data-first design

Every rule, clause, and policy are made actionable.

Governed logic

AI acts strictly within defined playbooks.

Reusable systems

Configure once, deploy anywhere.

Avo contract-based AI agents

Plug any LLM

Use OpenAI, Anthropic, or any LLM of choice.

End-to-end

Handle the full contract lifecycle with no tool-hopping.

Contract-based agents

Each agent is purpose-built for a contract type — NDA, MSA, DPA, etc.

Avo scorecard feature

Scorecard tracking

View every decision, rule, and confidence score.

Audit-ready logs

Every decision logged and timestamped.

Always improving

Optimize performance across teams.

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Orchestrate any contracting process

Get a seat at the strategy table and turn contracts into systems that drive execution across the business. Governed AI automates the manual work while you steer every decision with control.

Deal
Context

Use
Pre-sales discovery
Mutuality
Unilateral
Risk
Low 🟢
Perspective
Buyer

Document
Map

01
Parties
02
Definitions
03
Exclusions
04
Purpose
05
Return & Destruction
06
Governing Law
07
Signatures

Data
Model

We
Avokaado OÜ
Them
Business
#
Contract number
Signing date
Expiration date
List of data
Penalty
Jurisdiction

Decision
Rules

Penalty < €5000 → 🟢
Penalty > €5000 → ⛔
Jurisdiction is EU → 🟢
Jurisdiction not EU →⛔
No expiration date →⛔

Dialogue
Strategy

Tone
Formal
Stop
After 3 attempts
Rationale
Cite clauses

Deal
Context

Use
Partner onboarding
Risk
Medium–High 🟡
Perspective
Service Provider
Objective
Verify identity

Document
Map

01
Parties
02
Purpose of onboarding
03
Verification requirements
04
Beneficial ownership structure
05
AML / CTF disclosures
06
Data processing & retention terms
07
Risk acknowledgment & consent
08
Screening & ongoing monitoring obligations

Data
Model

We
Avokaado OÜ
Them
Business / Corporate Client
Beneficial Owners
#
Reference number
Dispute Resolution
Signing date
Review Frequency
Allowed Data & Retention
Penalties / Compliance Actions
Dispute Resolution

Decision
Rules

Missing mandatory documents → Reject
High-risk jurisdiction → Escalate
PEP match → Reject
AML Risk Score threshold → Approve
Approved onboarding Move to “Active Clients”
Review cycle due < 12 months → Auto-tag

Dialogue
Strategy

Tone
Professional & regulatory-aligned
Stop
2–3 attempts, then escalate
Rationale
Reference AML requirements and compliance procedures
Goal
Obtain correct documents, resolve discrepancies, and ensure compliancy

Deal
Context

Use
Vendor onboarding & ongoing management
Risk
Medium–High 🟡
Perspective
Buyer
Objective
Assess vendor risk

Document
Map

01
Parties
02
Scope of services
03
Service-level requirements
04
Data access & data protection obligations
05
Security & compliance certifications
06
Subcontractor restrictions
07
Liability, indemnity & insurance coverage
08
Performance monitoring & reporting
09
Renewal, amendment & termination terms

Data
Model

We
Avokaado OÜ
Them
Vendor Legal Name
Renewal Date
Review Frequency
Subprocessor List
Service Category
Data Access Level
Compliance Certifications
Insurance Coverage & Limits
SLA Targets
Jurisdiction & Governing Law

Decision
Rules

Missing certifications → Reject
SLA uptime < 99% → Escalate
Subcontractors not pre-approved → Block
Insurance coverage below threshold → Flag
Data access to PII without DPA → Reject
Vendors require annual review → Enforce Review Cycle
Risk Score < threshold → Approve

Dialogue
Strategy

Tone
Professional, compliance-driven
Stop
2–3 attempts, then escalate
Rationale
Cite security standards, procurement requirements, and internal policies
Goal
Collect missing information, resolve compliance issues

Deal
Context

Use
Vendor selection, RFP/RFQ evaluation, purchase approval
Risk
Medium–High 🟡
Perspective
Buyer
Objective
Standardize supplier assessment

Document
Map

01
Parties
02
Scope of Goods/Services
03
Technical & functional requirements
04
Pricing structure & commercial terms
05
Service-level expectations
06
Delivery & fulfillment terms
07
Compliance requirements
08
Warranty & support obligations
09
Termination, renewal & amendment terms

Data
Model

We
Avokaado OÜ
Them
Supplier Legal Name
#
Evaluation Score
Delivery Timeline
Renewal & Review Dates
Total Contract Value
Procurement Category
Commercial Model
SLA Requirements
Data Access Level
Governance & Stakeholder Approvals

Decision
Rules

Bid exceeds budget →  Reject
Missing documents → Block
Supplier risk score > threshold → Escalate
SLA < minimum requirements → Flag
Total contract value > approval limit → Trigger multi-level approval workflow
All criteria met + score ≥ threshold → Approve

Dialogue
Strategy

Tone
Structured, impartial, procurement-driven
Attempts
2–3 clarification rounds
Rationale
Reference procurement policy, scoring criteria, and best practices
Goal
Collect missing bid data, normalize proposals, identify best-fit supplier
Mariana Hagström
Mariana Hagström

Founder & CEO

Built for a world where legal can’t afford to guess

We see the same problem everywhere: AI that looks helpful but acts without accountability. Legal teams forced to recheck every line. Risk hidden in drafts no one could explain.
Legal locked into being a bottleneck, not a strategic function.

We're building Avo to change that. Not with another chatbot, but with governed AI infrastructure. Every decision verified, explainable, and aligned to your rules. Because legal AI should be as accountable as the people who use it.

Join the waitlist

Step into the future of legal work

Join the waitlist to get early access, exclusive benefits and see how governed AI agents can run your contracts end-to-end with full traceability and accuracy.


It's completely free and comes with no commitments.

Shape the future of legal AI together with us

Private beta access, including prototypes

Special, only-for-members offers

Exclusive launch event invite - first 50 members only!

Mystery gift - first 100 members only!

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Frequently asked questions

1. Do I need to be an Avokaado customer to join the waitlist?

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2. Who is Avo for?

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3. What happens after I join the waitlist?

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4. When will Avo be available?

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5. How is Avo different from other legal AI tools?

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6. How do I know the AI won’t make mistakes?

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7. Can I explain or audit what the AI does?

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8. Does Avo work with our current tools?

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9. Do we need to migrate our old templates or data?

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10. What can I actually do with Avo?

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11. Will Avo replace my legal team?

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12. How does this change the role of legal?

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13. Is Avo secure and compliant?

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14. Can I choose which AI model to use?

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15. How long does it take to get started?

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