The engineering team behind your hardest problems.Full-scale AI transformation, scoped and built on your solution, then delivered as production systems that run day to day

✕ Expertise 01

Industrial AI & predictive operations

The data your plant already produces, turned into decisions: failures predicted hours ahead, every unit inspected at line speed, and legacy systems finally answering questions

What we take on

• Predictive maintenance Vibration, thermal, current, and cycle logs modeled against your own failure history, so warnings land in the tools your team already uses
• Vision & quality Cameras, lighting, and triggers specced around your line (the 80% most vendors skip), models tuned to your defect economics, every unit checked
• Systems modernization We tap into existing PLCs, historians, and log files, with no forklift upgrade, and turn messy tags into one clean, queryable data model

How we approach it

1. Scope One line, one failure mode or defect class, one metric with a baseline
2. Build Models validated on your history, not a demo set, reviewed with your engineers as they take shape
3. Ship Alerts, reject signals, and dashboards wired into MES and existing controls, running on the edge if the line demands it

What you get

• Hours of lead time before failures, not minutes
• A measurable drop in unplanned downtime and escaped defects
• Models and data pipelines you own and can retrain as the plant changes

Typical timeline

Feasibility on your data in 2 to 3 weeks, a working pilot in 4 to 6, then rollout line by line

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✕ Expertise 02

Physical simulation & digital twins

Test the change before you touch the line. We build a model of your process that matches reality, then search it for the settings that cut energy, scrap, and cycle time

Where it fits

• Process optimization: setpoints that lower energy, waste, or cycle time
• Design iteration: CFD, thermal, and structural runs before the first prototype
• Digital twins: a living model you keep asking new questions
• Capacity planning: bottlenecks found in simulation, not in production

How we approach it

1. Model Physics plus your process history, calibrated until the model reproduces your real output
2. Search Thousands of what-if runs against the objective you actually care about
3. Validate Winning changes trialed on one line, measured against a baseline before anyone commits

What you get

• Changes proven in simulation before they hit production
• A clear before-and-after on your metric
• A twin your team reuses for the next question, without us

Typical timeline

A validated model in 4 to 6 weeks, then optimization runs against your targets

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✕ Expertise 03

E-commerce intelligence

Your catalog, your customers, your margin, modeled directly instead of approximated by an off-the-shelf plugin. The gains show up in conversion, basket size, and stock turns

What we take on

• Semantic search that understands your products the way your buyers describe them
• Recommendations tuned to margin and stock, not just clicks
• Dynamic pricing and promotion models with guardrails you set
• Demand forecasting that feeds purchasing, not a dashboard nobody opens

How we approach it

1. Scope One funnel metric (search conversion, attach rate, forecast error) with a clean baseline
2. Build Models on your catalog and behavior data, A/B tested against what you run today
3. Ship Integrated into your storefront and back office, monitored, with the experiment framework left behind

What you get

• A measured lift, not a vendor's case-study number
• Models that keep learning from your traffic
• Full ownership, no per-request fees to a black box

Typical timeline

A live A/B test on real traffic in 4 to 6 weeks, then iterate on what the numbers say

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✕ Expertise 04

Private & on-prem AI

All the capability, none of the data leaving your site. We deploy on your hardware, harden it, and hand you the keys

How we approach it

1. Right-size Model matched to silicon, from a rugged edge box to your existing GPU nodes. Bigger is rarely better once it's your power bill
2. Harden Offline first, monitored, updatable without exposing anything to the public internet
3. Hand over Documentation and training so your team runs it without us in the loop

What you get

• Full data residency, nothing leaves the building, auditable
• Predictable latency and a cost that doesn't scale with every request
• No vendor lock-in on models, weights, or deployment

Typical timeline

A reference deployment in 3 to 5 weeks, then replication across sites

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✕ Expertise 05

Custom builds

The same delivery rigor, pointed at whatever your team needs built. If it involves data, models, or automation, we can ship it

What we take on

• Private LLM tooling on your own documents and data
• Document and knowledge extraction into structured output
• Internal automation that removes repetitive work
• Integrations between systems that don't talk to each other

How we work it

1. Scope One clear outcome and how we'll measure it
2. Build A working version in weeks, on your stack, reviewed with you as it goes
3. Hand over Documented, tested, and yours to run

Typical timeline

Most first builds ship in 4 to 8 weeks, depending on scope and access

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✕ Expertise 06

AI strategic transformation

Not a deck about AI, but a sequence of shipped systems. We audit what you have, rank opportunities by payback, and prove each one in production before scaling the next

How we approach it

1. Audit Two to three weeks inside your data, systems, and workflows. Output: a ranked map of opportunities with effort and payback attached
2. Pilot The top two or three, built in parallel on real data, killing fast what doesn't pay
3. Production Winners shipped, instrumented, and owned by named people on your side
4. Scale A repeatable playbook and, if you want it, your own team trained to run the next wave

What you get

• A roadmap where every line item has running code behind it
• Honest kill decisions: we'd rather stop a pilot than scale a mistake
• Internal capability, so the second wave doesn't need us

Typical timeline

Audit in 2 to 3 weeks, first pilots live inside a quarter, production wins inside two

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