Better decisions.
Real progress.

Avery Intelligence
Independent applied AI
& product lab
Menlo Park, California

We help organizations decide what’s worth building—and make it work.

Three ways to work with us.

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Our view

01

Better decisions. Real progress.

It is becoming easier to produce an answer, a document, or a working prototype. It is still difficult to know whether it solves the right problem. More output can leave an organization with more to reconcile, rather than a clearer sense of what to do.

We believe the next useful layer of AI will connect what an organization knows, what it has decided, and the work that follows. That requires product judgment as much as technical capability.

Context is part of the system.

A capable agent needs more than a task. It needs to know which goal matters, what has already been decided, and where the evidence comes from. We think that context should be explicit, connected to its sources, and open to correction by the people responsible for it.

A recommendation should be open to challenge.

A persuasive explanation is only a beginning. The alternatives, the economics, and the assumptions deserve the same attention. We make the call explicit and show what could change it. Sometimes the useful answer is to make a smaller commitment, use an existing tool, or stop.

Responsibility stays with people.

AI can accelerate the work. Someone still needs to understand the tradeoffs, own the recommendation, and see the result through. At Avery, responsibility is explicit. Each engagement connects an accountable lead with the expertise, evidence, and authority the work requires.

Useful work changes what happens next.

A memo belongs in a real decision. A prototype should resolve an uncertainty. A delivery engagement should move a funded priority forward. We judge the work by what it enables people to do.

The applied lab

02

We build the systems we think about.

Our own product, Humfrid, grew out of a problem we encountered in our work: AI agents could execute tasks, but kept losing the company context that made those tasks matter.

Humfrid makes goals, decisions, and operating principles source-linked and editable. People can access that context in Slack; agents can use it through MCP. A continuous loop connecting goals, action, and evidence is in development.

Building gives our advice a practical foundation. It exposes the integration, context, and operating questions that a demonstration can leave unanswered.

Inside the lab

The practice

03

Three ways to work with Avery.

Buy the result you need: a recommendation, ongoing delivery ownership, or a working prototype. Each engagement has its own scope; you can start with any of the three.

Decision Factory

$3,000 USD

A consequential decision. A sharp second opinion. We pressure-test a product or AI recommendation before you commit, and give you a clear call, the evidence behind it, and what would change our view.

One-page recommendation, supporting evidence, and a discussion of the recommendation. One decision, fixed scope, and a delivery date agreed before payment.

Explore the review

Embedded Delivery

From $10,000 USD/month

A funded workstream needs an owner. We take ongoing responsibility for product decisions, priorities, and delivery coordination inside your team or agency engagement. Your engineering team owns the build.

Start with a $5,000 scoped stage, up to 25 combined delivery hours. Ongoing work starts at approximately 50 combined hours per month. If the stage forms part of the first month, its fee and hours are included.

Explore delivery

Prototype Lab

Scoped project · custom quote

Your external skunkworks for a consequential AI product bet. We take a bounded idea through to a working prototype and the evidence to decide what deserves further investment.

Use our existing technology, build something new, or combine both. Avery owns the contained build. You receive the agreed prototype, evaluation findings, and a technical handover. Delivery under your brand is available by agreement.

Explore the lab engagement

A decision, examined

04

A convincing AI pitch. A different answer.

The vendor’s story: automate support and recover time. The question: does the recoverable value justify the first-year cost?

DECISION FACTORY / BRIEF 001ILLUSTRATIVE CASE

Do not approve the rollout as proposed.

First-year cost$164,000
Annual capacity value$50,400

The recommendation turns on how much of the work is actually eligible.

Inspect the assumptions

A fictional case with an interactive model. Capacity value is not cash savings.

Avery Intelligence

05

Product judgment. Applied intelligence.

Our experience spans product leadership, growth, and hands-on AI systems. We bring those disciplines into the same work: understanding what matters, testing what is possible, and seeing the result through.

That work also brings us into conversation with leaders facing the same questions. At a recent SAP Signavio product leadership offsite, we examined what shared company context could mean for an AI-native product team.

We are based in Menlo Park and work with founders, product and technology leaders, and agencies with funded delivery needs. Initial conversations are welcome in English or Swedish.

About Avery

What are you working on?

Bring us the decision, the delivery gap, or the capability you need.

Contact the lab