The Forward-Data Process — our flagship
The uncrowded, decision-grade data you should be building for the decisions you're about to face — found, validated, and frozen accountably.
Most companies collect data for where they've been, then find they never captured what the next decision needs — and you can't backfill data you didn't collect. We design, build, extract, and validate what you should be measuring nowfor the decisions ahead: the framing, the experiment, the signal, and a signed, hash-verifiable record — so the data you build is decision-grade, not vanity.
Start with the free Data Bottleneck Snapshot — see where your data work bottlenecks before you spend anything.
Why now
The baseline you need to prove an effect, the clean comparison group, the outcome measured at the right grain — those only exist if you started capturing them beforethe change. Data designed now for where you're going becomes a uniquely valuable, decision-linked, time-series asset — one that can't be assembled after the fact, because the observations only exist if they were captured at the time. The deliverable ships and is paid for now; the data compounds as you collect it.
How it works
We pin the true-north decision you're about to face, the hypotheses it forces, and the counterfactual — what the data has to settle, and what it would look like if the bet is wrong — before any data moves.
Sampling, causal-design selection (A/B, staged rollouts, holdouts, quasi-experiments), power and sample sizing, and exactly what to instrument — the engine for building the right data, not vanity volume.
We extract the weak predictive signal from the noisy, high-dimensional data — finding what's actually there is the core competency, and the uncrowded signal is the durable one.
Pre-registration → out-of-time / out-of-sample → permutation → negative controls → multiple-testing correction. Every claim is independently checked and reproducible — not a promise, a proven result.
We measure that the signal is orthogonal to the crowded consensus — a durable edge, not a re-derivation of what everyone already has. Less crowded data means a more durable edge.
The design and the result are frozen into a signed, dated, hash-verifiable record. Anyone can verify what was committed to before the data came in — that is the accountability.
What you get
Every data stream traced to the decision it serves and the threshold that should trigger action — so nothing you collect is vanity.
The causal design and the sample sizing (power analysis) for each hypothesis, plus the instrumentation and schema to capture the right data at the right grain.
The weak predictive signal found in your data, tested out-of-sample and proven uncrowded — orthogonal to the crowded consensus, so it's a durable edge rather than a re-derivation.
The design and the result frozen into a signed, dated, hash-verifiable record. Anyone can verify it wasn't edited after the result came in — that is the accountability.
Also
Sometimes the bottleneck isn't what you'll measure next — it's the quality of the data you already hold. We clean it to a different standard, then prove on your own de-identified data whether that cleaning actually beats what your current pipeline produces — on a held-out window frozen before we touch it: same model, same metric, only the data changes. You keep the result and the evaluation protocol; the cleaning method stays ours.
We don't claim a number. On a window frozen before we see it, we measure whether the cleaned data actually beats both your current data and a standard cleaning recipe — and show you the result. We offer to prove the lift on your data; we never promise a future outcome.
Better data can be a genuine, hard-to-copy advantage — or just the tidy-up anyone could do. The two look alike on a quick read, so we measure which one your cleaning actually is and tell you honestly. You won't pay for an advantage that isn't really there.
You see the measured lift, the metric, the held-out window, and a dated, hashed record of exactly what we committed to test. The cleaning recipe itself stays our background material — what you buy is the measured result on your held-out window — which may be that the lift isn't there — not the recipe.
The same accountability you get on a forward design — a dated, hashed, pre-registered record — applied to the data you already have. See how we prove it.
Why us
Anyone can run a power calculation. The difference is a signed, dated, hashed record of exactly what you committed to measure — and why — frozen before the data came in. When a board, a partner, a regulator, or a journal asks “did you decide this in advance?”, you can prove it. A free model can give you a number; it can't stand behind one.
The design, sizing, pre-registration, and validation run on our autonomous agent fleet, with our team in the loop for the judgment. So you get research-grade measurement design without a big-consultancy price — we don't sell you agents, we are your agents.
How it's scoped
The Data Bottleneck Snapshot is free — the no-commitment place to see where your data work bottlenecks and how we'd unblock it.
Scoped to your decisions, with every fee agreed before we start. The finished, validated work — decision map, experiment design, the extracted signal, and an accountable freeze — ships now; nobody buys a deferred forecast on faith.
As the data matures, an optional retainer tests the pre-registered hypotheses and delivers validated decision memos — metered per analysis cycle, not per month of waiting.
Scope and price are agreed before any work begins, in writing, alongside the full terms at services terms.
The fine print, in plain English
We design measurement for operational and process decisions — never markets, returns, or capital allocation. We design and validate; we do not provide financial or investment advice.
You own your deliverable, your data, and the specific result we build for you, assigned on delivery. We retain our generalized, anonymized methods and tooling as our own background material.
Hypotheses and kill criteria are frozen and dated before collection. A hypothesis coming back false is a valid result, not a miss — that's the point of testing.
Tell us where you're going and the decisions that matter. We reply within two business days with what you'd need to start measuring and how we'd scope it. Not sure yet? The free Snapshot is the no-commitment place to start.
Who you'll work with
Founder & Chief Executive Officer
“Good research is built from creativity, breadth, and empathetic learning from others.”Meet the team
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