Custom models engineered for ROI
Predictive, vision and NLP models built around a business metric — not a benchmark — and shipped to production where they earn their keep.
every model targets a KPI — and ships to production
/ what actually counts
Accuracy isn’t all.
Your number is.
A model can top every benchmark and still move nothing. We engineer each one around a business metric you already track — so it earns its keep, not a leaderboard rank.
/ what it’s worth
Every $1 in AI,
$3.70 back
The return is real — but it only shows up when the model moves a metric your business already lives by. That’s the only kind we build.
return on every $1 invested in AI
IDC / Microsoft, 2024
…but only when the model is tied to a number you already track. A leaderboard win returns nothing.
/ the model’s P&L
What a model
is worth
Churn is one example — drag in your numbers and watch the revenue a retention model protects.
Revenue at risk from detectable churn / year
You keep / year
$1.8MAt-risk customers (detectable) / year
1,500 keptCutting churn 20% keeps ≈ 1,500 customers — ≈ $1.8M a year.
/ proof, not leaderboards
Proven on your data,
before you bet on it
We don’t chase leaderboard accuracy. We prove the model on your real, held-out data — measured against today’s baseline and the KPI it has to move — before a single decision rides on it.
a number you can trust — not a black box
/ how we ship it
Built to ship,
from line one
Most models die in a notebook because no one planned for production. We work backwards from the KPI, and every step earns its place on the way to a live, monitored model.
Frame the KPI
Start from the number you want to move — not a model type.
Baseline
Measure today's cost and performance, so impact is provable.
Engineer & train
Features, model and tuning — on your real, messy data.
Validate
Held-out, real-world tests against the baseline before rollout.
Ship & monitor
Into production with drift detection and a retraining path.
/ why it pays
Outcomes you can measure
model accuracy
Predictive models
Forecasting, churn, demand and risk models tuned to your decisions and data.
faster inspection
Computer vision
Detection, inspection and OCR that automate what humans can't do at scale.
less manual review
NLP & search
Classification, extraction and semantic search over your unstructured text.
AMDIM delivery · McKinsey 2024 · AMDIM engagements — verified, not invented.
/ what we deliver
End-to-end, not half-built.
/ the depth
Beyond the basics —
the full toolbox
6 capabilities, each backed by a real toolbox — classical to deep / advanced. A taste below; the full library runs deep.
techniques · 17 disciplines
Predict
what happens next
Decide
the best next action — causally
Connect
networks, fraud & relevance
Perceive
vision, speech & documents
Quantify uncertainty
how sure — and why
Learn efficiently
with less data — tuned & trusted
/ your industry
The hard problems
that actually pay
Every sector has a handful of problems that are genuinely hard — and genuinely worth it. Pick your industry for a taste; the full set lives on the industries hub.
Manufacturing
why it’s hard — Defects are rare events on fast lines; models run at the edge in real time, with near-zero tolerance for a missed fault.
$50B/yr lost to unplanned downtime (Deloitte); AI-in-manufacturing ~35% CAGR to 2030 (Grand View).
Sub-pixel visual defect detection at line speed
Vision catches hairline cracks and voids too fine for the eye, while the line keeps moving.
One missed hairline crack ships a recalled part.
evidenceInspectors miss 20–30% of defects; AI vision hits 95–99% (iFactory)
Remaining-useful-life on rotating assets
Forecast the hours left on bearings and spindles from vibration and thermal signatures.
The line that dies mid-shift costs six figures an hour.
evidencePdM cuts downtime up to 50%, maintenance cost 10–40% (McKinsey)
Root-cause across multivariate process drift
Causal/graph models pinpoint which upstream parameter broke the batch, not just correlate.
200 sensors moved; only one broke the batch.
evidenceUnplanned failures cost ~$260k/hour on average (Siemens)
/ before you commit
Fair questions
Whatever ships fastest and safest — we fine-tune proven open models when we can, and build bespoke only when the problem demands it.
See where you stand in 5 minutes.
Take the AI/ML Solutions Readiness Scorecard — a tailored score and the fastest path to impact.
/ explore more