Customer.
What is actually working.
Four numbers. One gap.
i.
The room
Everyone has AI. Almost no one has shipped it.
When asked, eighty-eight percent of organizations say they have AI somewhere in their business.
Ten percent of staffing firms say they have shipped it end to end.
Ninety-four percent of workers say their company is not making real progress with it.
Only eight percent of job seekers say AI screening makes hiring fairer.
Sources.
- 88%McKinsey, The State of AI 2025 · Organizations using AI in at least one business function.
- 10%Bullhorn, GRID 2026 Industry Trends Report · Staffing firms that have implemented agentic AI across full workflow.
- 94%Deloitte, 2025 Global Human Capital Trends · Inverse of the six percent who report real progress on AI value.
- 8%Greenhouse, 2025 AI in Hiring Report · Job seekers who believe AI screening makes hiring fairer.
ii.
What the market believes
The world is moving.
The four biggest tech companies put nearly half a trillion dollars into AI infrastructure last year.
Their AI spending is now larger as a share of US GDP than Apollo, the Interstate Highway System, and the Manhattan Project combined.
In the first half of 2025, AI capital spending drove more US GDP growth than American consumers did.
That is what the market believes AI is capable of. Whether that belief lifts or harms depends on how the work is built.
Sources.
- ~$450BEpoch AI, hyperscaler capex analysis from SEC filings · Combined 2025 capex of the largest US technology companies.
- GDP shareCreditSights via IEEE ComSoc Technology Blog · Big tech capex as share of US GDP, compared to Apollo, Interstate, and Manhattan as shares of GDP at their respective peaks.
- 1H 2025 growthKKR, Beyond the Bubble: Why AI Infrastructure Will Compound Long After the Hype · AI capital spending contributed more to US GDP growth in the first half of 2025 than consumer spending did.
iii.
What we believe
AI extends human reach when three things are real.
When they are not, AI compounds error. We have learned this from the lift and from the harm.
Augmentation, not autonomy.
Fei-Fei Li, Stanford Institute for Human-Centered AI. Twenty years of consistent framing.
The center of the work is human-centered AI. AI augments the work humans do. AI does not replace the human doing the work. The I in HAI is augmentation, not autonomy.
The jagged frontier.
Ethan Mollick, Wharton. Navigating the Jagged Technological Frontier, 2023.
On tasks the model is good at, AI lifted seven hundred and fifty-eight Boston Consulting Group consultants by roughly forty percent in quality. The lowest performers gained the most. On tasks the model was over its skis, the same consultants were nineteen points more likely to get the wrong answer. The capability boundary is invisible from inside the tool. Same tool. Same workers. Different problems.
Three things.
The difference between the lift and the harm is whether the work has all three.
A person in the chair.
A human can stop or change the decision. Not AI suggested it, the system did it. A person was in the chair when the decision happened, and that person can say no.
A receipt with their name on it.
Someone can show what happened. Who decided. What they saw. What the system said. What the human did with it. Not just the answer. The trail behind the answer.
An answer the worker can read.
The person on the receiving end can find out why. Not legalese. Not the algorithm said so. A reason they can read, in language they understand, that matches what actually happened.
AI cannot be in charge of work. It extends the work a human is doing. The full evidence is in a separate essay.
iv.
What we built
Almanak is the front. Cassion is the working layer underneath.
What you read above lives in the architecture we built. The three things are real by design. The surface is one product. The layer underneath is a few moving parts.
The surface.
Almanak is the daily companion. One product on the phone and on the web. Capabilities surface by role and context, not by device. Same identity, same dignity floor, same audit substrate across every screen. A worker meets Almanak. An operator meets Almanak. A customer staff member meets Almanak. Same product, same standard, no calcified hierarchy.
The substrate.
Cassion is a governed data foundation. Every write is recorded. Every record can be traced to the human, agent, or system that made it. The audit is the spine. Privacy and accessibility commitments are enforceable because the audit is enforceable.
The orchestrators.
Orchestrators are the work humans already do. The recruiter who screens. The scheduler who books. The operations lead who runs the floor. They already orchestrate the data, the rules, and the patterns inside your stack. We do not replace them. We learn from them.
Number One.
Number One is the model that mirrors the orchestrators. Ten mirrors, one for each orchestrator we know about. Number One watches the orchestrator at work, learns the pattern, and powers the work where you let it. When Number One struggles or sees a case it has not seen, it escalates to a human. The escalation is the feature, not the failure.
The Compass.
The Compass holds the rules. Your rules. The customer keeps the policy authority. The Compass is anchored to the work the orchestrators are already doing, not to a standard we imposed. Where your rules and the law differ, the law wins. Where your rules and our human standard differ, we tell you, and you decide.
Model Card+++.
Every decision in the system has a card. The card records the seat that held the decision, the data that informed it, the rule that bounded it, the override if there was one, and the answer the affected human received. The card is the receipt.
Every edge is a decision. We do not replace your stack. We add the mirror, the substrate, and the audit. You keep what is working. We replace what is not. You decide which is which.
v.
The ask
We need first customers.
We are not in the staffing business. We are in the workforce machine business. We have not done this before at this size, and we are honest about that. We are reading the people who have, we are listening to the advisors who have been on the floor, and we are building this in the open.
What we need now is first customers. People willing to run a real engagement with us, with the terms disclosed in full before any work begins. The first few become the reference for everyone who follows. We are choosing them carefully, and we want them to choose us the same way.
Be a customer.