AI & Applied Intelligence
Vision inspection, predictive maintenance, agentic systems and LLM applications — designed with evaluation, guardrails and governance from day one.
Explore practiceAltQube moves applied intelligence out of the lab and into the places it changes numbers — the plant floor, the risk engine, the product your customers actually use. Deepest in automotive and manufacturing, with fintech and AI-native product teams close behind.
AI is the through-line — but intelligence only compounds when the data, platform and product beneath it are engineered properly. We do all of it, with the same senior team.
Vision inspection, predictive maintenance, agentic systems and LLM applications — designed with evaluation, guardrails and governance from day one.
Explore practiceLakehouse architectures, streaming pipelines, data contracts and semantic layers — the foundation every credible AI program stands on.
Explore practiceProcess mining, intelligent document processing and agentic workflows — from supplier onboarding to warranty adjudication, with humans in the loop where it matters.
Explore practiceMigration, platform engineering, SRE and FinOps across AWS, Azure and GCP — built so your teams ship faster and your run-rate goes down.
Explore practiceAI-embedded products for web and mobile — discovery, design systems and delivery by cross-functional pods that own the outcome.
Explore practiceDemand, capacity, pricing and network optimization — models with documented assumptions and quantified confidence, built for decisions that carry real cost.
Explore practiceEvery engagement is measured against a business metric agreed before we start. Here are three from automotive and manufacturing floors.
Replaced a fatigue-prone manual booth inspection with a vision system that catches orange peel, runs and dirt inclusions at full conveyor speed — cutting rework and warranty exposure.
Vibration, current and temperature telemetry fused into a model that flags bearing and die failures days ahead — letting maintenance land in planned windows instead of stopping the line.
Language models over unstructured dealer notes and technician comments surface emerging failure patterns weeks before they appear in structured warranty codes.
They walked the shop floor before opening a laptop.
“We'd already burned eighteen months on AI pilots that never left the slide deck. AltQube was the first partner that walked the shop floor before opening a laptop — and had something running on the line inside a quarter.”
Head of Digital Manufacturing · Passenger vehicle OEM, India
Not every problem needs a model. When you need experienced engineers, a managed delivery pod, or specialist skills at short notice, we staff from the same senior bench that runs our AI work — so quality never drops between engagement types.
Automotive and manufacturing are our home ground. Fintech and AI-native product teams are where that same rigour transfers most directly — reference architectures and evaluation datasets you don't pay us to acquire.
Body shop, paint, assembly, quality gates and launch readiness.
Machining yield, traceability, PPAP evidence, customer scorecards.
OEE, predictive maintenance, vision inspection, energy intensity.
Supplier risk, inbound planning, route and network optimization.
Parts demand, warranty analytics, dealer and service intelligence.
Credit risk, fraud detection, underwriting and reconciliation.
AI-native applications, copilots and intelligent platforms.
Telemetry platforms, fleet intelligence, EV battery analytics.
Most failed AI programs failed at framing, not modeling. We front-load the hard questions so the build phase is boring — in the best possible way.
We start with the business decision you're trying to improve and the metric that proves it. If AI isn't the right lever, we'll tell you in week one — that's cheaper for both of us.
An honest audit of what your data can actually support today. Most roadmaps break here, so we surface the gaps before they become a delivery risk instead of after.
One narrow, end-to-end path to production in weeks — with an evaluation harness, not a demo. Real users, real data, real failure modes, measurable baseline.
Observability, guardrails, cost controls, human-in-the-loop design and a governance model your risk function will actually sign off on.
Documentation, runbooks and paired delivery so your team can operate and extend the system without us. Dependency is not our business model.
Plant heads, quality leads and CIOs — in their words. Hover to pause.
They pushed back on our original scope and proposed something smaller and sharper. It shipped in seven weeks and paid for the whole engagement inside two quarters.
Our quality team was sceptical about vision inspection — they'd seen two failed attempts. AltQube ran it in shadow mode for six weeks until the line supervisors trusted it themselves.
The evaluation framework they built is now how we assess every AI vendor that walks through the door. That alone changed how we buy.
Downtime on our press line used to be a monthly firefight. It's now a planned maintenance conversation. That shift is worth more than the model itself.
We engaged them for engineers and ended up with an advisory relationship. The people they placed were genuinely senior — no bait and switch.
Forecast accuracy went from something we argued about to something we plan against. Our safety stock came down without a single stockout.
They spent the first week on the floor with our technicians, not in a boardroom. It showed in what they built.
Handover was genuine. Six months on, our own team is extending the platform without calling us back into a support contract.
Start small and prove it, or bring us in to own a program end to end. Every model is priced against a defined outcome.
A partner-led diagnostic that separates the use cases worth funding from the ones that sound good in a board deck.
One high-value use case taken from framing to production, with an evaluation harness and a measured baseline.
A cross-functional squad that plugs into your delivery org and owns a roadmap alongside your own teams.
Senior counsel on architecture, vendor selection and AI governance — without carrying the headcount.
Send a short brief and a partner will respond within one business day with an initial point of view — and an honest read on whether we're the right firm for it.