AI Contract Architecture Advisory
Enterprise buyers don't block AI products because of the technology.
They block them because the commercial infrastructure isn't there yet. Your product works. Your contracts don't reflect how it actually operates. That gap is the ceiling on enterprise deployment, institutional investment, and defensible scale.
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Who This Is Built For
You've built the agent. Now build the layer that lets it actually deploy.
The Gap That Kills Deals
You're building a product where AI does real work: autonomously, at scale, inside your customers' most important workflows. You're signing enterprise deals, talking to investors, and moving fast.
Your commercial agreements were probably drafted for a software business. They don't reflect how your agent actually operates: what it decides, what data it touches, which model it calls, and who is accountable when something doesn't go as expected.
That gap is the ceiling. It's what kills a deal in the final week of enterprise procurement. It's what an investor finds in diligence that delays a raise. It's what turns a model error from a support issue into a contract dispute.
The Trust Layer
The product isn't the problem. The trust layer underneath it is.
Venture Bench builds that trust layer. Not compliance for its own sake. The commercial infrastructure that makes your product deployable, your deals closable, and your business investable at the next level.
Founder and Principal, Venture Bench
Carly Martin (Linkedinbio)
Ex-Amazon global expansion business lead and magic circle top tier lawyer. I've been on both sides of enterprise deployment at scale. I know what gets deals over the line and what stops them dead.
I know what enterprise procurement teams ask for when evaluating AI products. I know what makes a business look trustworthy to an institutional investor versus what raises flags. And I know the difference between a contract stack that scales and one that becomes the ceiling.
AI Product Risk
Enterprise Procurement
Capital Raising
m&a/exits
international expansion
Diligence Findings
What Diligence Finds, And What It Costs You
Every gap in your commercial infrastructure is a line item in someone else's valuation model. These aren't hypothetical risks. They're the patterned findings that appear in diligence on AI-native businesses.
Liability
When your AI gets it wrong, your contract decides who pays. Standard liability caps were designed for software that does what you tell it. If your product makes decisions autonomously and something goes wrong, the cap you have may not apply the way you think it does.
IP Ownership
The IP your product generates may not belong to you. Enterprise customers push hard for ownership of AI-generated outputs. If your agreements don't address this explicitly, the default position under Australian law may not be what you'd expect.
Data Risk
Your product uses an external AI API. Your contracts probably don't say that. If you're calling OpenAI, Anthropic, or any other foundation model API with customer data, you're a data sub-processor. Enterprise security reviews will find this.
Model Risk
Your model provider can change their pricing, deprecate your model, or go down. And your SLA still runs. If your product is built on a third-party foundation model and your customer contracts don't include substitution rights, you can be in breach of your own SLA.
Regulatory
What your contracts say about accuracy and your actual AI behaviour may not match. If your agreements include representations about accuracy and your product's actual behaviour isn't fully documented, that gap is a warranty problem.
Procurement
Enterprise procurement teams are now asking for AI transparency documentation, autonomy level disclosures, and liability allocation frameworks as standard. Your contracts can't answer these questions yet.

The compounding problem: Every enterprise deal you close on inadequate terms raises the ceiling a little higher. Every investor conversation you have without clean commercial infrastructure creates friction. The time to build the trust layer is before you need it, not when you're already in the negotiation.
Framework
The ARAF Framework
Before we build anything, we map what you've actually deployed. Five dimensions that determine what your commercial infrastructure needs to do, and what your current agreements don't cover. Every engagement starts here.
"The thing that stops great AI products from deploying at scale isn't the technology, it's trust. Enterprise buyers need to trust that your product is accountable."
Ken Shaw, Founder of Sapience
1
Autonomy Gradient
How much your product operates without human sign-off
2
Contract Infrastructure
Whether your agreements match your risk profile
3
Data Sensitivity Exposure
What data your agent processes and what it triggers
4
Model Dependency Risk
Upstream exposure to third-party model changes
5
Enterprise Concentration
Single-point-of-failure risk from key customer terms
To review the ARAF Public Framework, click here
Framework
The ADA Framework
The ADA outlines the engineering and architectural patterns required to build robust, resilient, and recoverable AI agents. It addresses the inherent non-determinism of AI and ensures your product can operate reliably in enterprise environments.
"Value doesn't come from launching isolated agents. 2026 will be the year we begin to see orchestrated super-agent ecosystems, governed end-to-end by robust control systems that drive measurable outcomes and continuous improvement." Source: KPMG Q4 AI Pulse Survey, January 2026
Chandrasekaran, Global Head of KPMG AI and Data Labs
Agentic Failover
Seamlessly manage model or API failures, ensuring continuous operation and graceful degradation when issues arise.
State Persistence
Architect state management to guarantee agent context and progress are never lost, even across restarts or reconfigurations.
Observability & Audit
Implement comprehensive logging and tracing for every agentic action and decision, crucial for debugging, compliance, and trust.
Versioning & Rollback
Enable safe deployment of agent updates with the ability to revert to previous versions, minimizing disruption and risk.
To explore the Agentic Durability Architecture in detail, click here .
What We Build
AI Contract Architecture: Six Things We Build For You
Liability Framework
Designing the liability framework for your AI outputs: caps, exclusions, error allocation, and where your responsibility ends and your customer's begins. Calibrated to what your product actually does, not a generic software template.
IP Ownership Architecture
Drafting clear ownership provisions for the outputs your agent generates: covering customer ownership claims, your own IP retention rights, and the specific IP risk created by training data feedback loops.
Data Flow Visibility
Building the data processing agreement and sub-processor framework that reflects how your product actually handles data, including the AI APIs it calls, so you can pass enterprise security reviews without renegotiating every deal from scratch.
AI Transparency Brief
The document that lets your product show its work. How your agent operates, what it can and can't do, who's accountable, and how you handle errors. Enterprise procurement asks for it. Investors look for it. We build it once; you produce it whenever it's needed.
Enterprise Negotiation Support
When an enterprise customer redlines your liability caps, IP ownership clauses, or data processing terms, you need someone who knows which positions to hold, which to trade, and how the negotiation affects the architecture underneath.
Investor Diligence Readiness
Investors doing diligence on AI-native businesses are now looking specifically at commercial infrastructure. A clean stack isn't just defensive. It's a signal that you're ready for institutional capital.
Results
What the Trust Layer Delivers
Representative outcomes from engagements with AI-native businesses deploying into enterprise.
8wks
Faster Procurement
Enterprise procurement cycle compressed from 14 to 6 weeks by delivering a complete AI commercial infrastructure pack at RFP stage. Agentic SaaS, Series A.
3
Deals Closed
Enterprise contracts closed in a single quarter after rebuilding liability, IP, and data flow architecture from template-based agreements. Autonomous analytics, Pre-raise.
0
Diligence Flags
Investor diligence completed with no commercial infrastructure findings. The first clean pass the lead investor's counsel had seen on an AI-native deal. Foundation model product, Series B.
$2.4M
Exposure Reduced
Estimated exposure reduced by restructuring liability caps and model substitution rights across existing enterprise contracts. AI workflow automation, Growth stage.
How It Works
Understand What You've Built. Then Make It Deployable.
We don't start drafting before we understand your risk profile. Every engagement begins with the ARAF diagnostic, because the architecture needs to match what your agent actually does, not what a template assumes it does.
The process is designed to match the architecture to your actual risk profile, not a generic template. Each step builds on the last, so the trust layer is coherent from diagnostic through to ongoing operation.
Engagement Options
How We Work Together
Four entry points, one diagnostic foundation. Every engagement starts with the ARAF diagnostic. Pricing is scoped after that conversation, not before it.
Starting Point
Agentic Risk Snapshot
Rapid diagnostic for early-stage or pre-raise
  • ARAF diagnostic across all 5 dimensions
  • Autonomy gradient classification
  • Top 3 structural risk findings
  • Prioritised action plan
  • Credited toward full ARAF audit
Comprehensive
Full ARAF Audit
Comprehensive risk profile and architecture roadmap
  • Full 5-dimension ARAF diagnostic
  • Complete structural risk report
  • Architecture gap analysis
  • Enterprise readiness assessment
  • Investor diligence readiness memo
  • Recommended contract architecture plan
Full Build
AI Contract Architecture Build
Complete commercial infrastructure
  • Full ARAF audit included
  • MSA with AI-specific provisions
  • DPA and sub-processor framework
  • AI Transparency Brief (enterprise-ready)
  • Liability and IP architecture
  • Enterprise negotiation playbook
Add-on
AI Risk Retainer
Monthly engagement keeping your contract architecture current as your product evolves, your enterprise deals get more complex, and the regulatory environment changes. Includes a direct line when a deal gets complicated.
Add-on
Enterprise Negotiation Support
Scoped per engagement. For when an enterprise buyer redlines your liability caps, AI terms, or data processing provisions and you need a lawyer who understands your product, not just your contracts, in the room.
Beyond the Build
The Trust Layer Is the Foundation
For companies ready to move further, we work across the full lifecycle, from board-level governance to capital strategy.
Board and Governance Advisory
Your commercial infrastructure needs board-level visibility. We help AI-native companies establish governance frameworks, board reporting structures, and the institutional muscle memory needed to manage AI risk at scale, including geopolitical exposure, model dependency, and regulatory readiness.
Capital Raise Readiness
Clean commercial infrastructure is the on-ramp to institutional capital. When your trust layer is built, we can help you pressure-test your investment thesis, refine the capital narrative, and position the business for a structured raise, with introductions to investors who understand AI-native businesses.

Board advisory and capital raising services are delivered through separate engagement structures.
Value Perspective
What You Would Pay for the Same Work Elsewhere

The compounding cost of waiting: Every enterprise contract you sign on inadequate terms sets a precedent your next deal has to work around. The trust layer costs less to build before you need it than after the deal falls through.
Book Your Diagnostic
Book a 20-Minute Diagnostic Call
Tell us what your product does and where your deals are getting complicated. We'll give you an honest view of what the trust layer needs to look like, and what it doesn't. No obligation; just a clear picture before you decide anything.
Who we work with: Founders deploying AI products into enterprise and institutional workflows: agentic SaaS, autonomous tools, products built on foundation models, at Series A/B, or pre-raise and building toward it.
VENTURE BENCH
AI Contract Architecture Advisory · Venture Bench Pty Ltd · ABN 55 676 334 213
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