Labs · AI Labs · Applied research
AI Labs is WNC’s research arm. We turn frontier AI into systems your business can actually rely on — agents, RAG pipelines and voice that run in production, built by the same engineers behind our own products.
01 / The problem
The gap between an impressive demo and a system you can trust in production is where most AI work dies. We live in that gap.
Models that look great in a notebook but never survive contact with production traffic.
Without retrieval, evals and guardrails, AI output is impossible to trust at scale.
Prototypes stall when there are no engineers to ship, monitor and maintain them.
02 / Retrieval
Every answer is grounded in your sources and cited — so your team can trust it. This is the retrieval pipeline behind it.
Docs, DBs & APIs
Chunk & vectorise
Relevant context
Grounded answer
Sources attached
03 / Compared
| WNC AI Labs | Generic agency | Freelancers | New in-house hire | |
|---|---|---|---|---|
| Ships to production | ||||
| Owns cloud & AI infrastructure | ||||
| Has its own AI products in market | ||||
| Senior engineers, no handoffs | ||||
| Agents, RAG & voice expertise |
04 / Capabilities
From the model layer to the product around it — one senior team, end to end.
Tool-using agents that plan, act and complete real workflows — not just chat.
Pipelines that ground models in your own data with citations and evals.
Speech recognition, speaker memory and natural text-to-speech, on-device or cloud.
Private, offline-capable models that keep sensitive data on your machines.
GPU inference, scaling and observability on AWS with NVIDIA acceleration.
We upskill your team through WNC Academy and hands-on advisory.
05 / Factory optimization
Take a frozen-vegetable plant. The line runs fast, the product is never identical twice, and every percent of waste, downtime or wasted cold is money out of the door. That is where AI pays for itself.
On an IQF line — individual quick freezing — vegetables run from intake through washing, blanching, the freezing tunnel and grading in minutes. The cameras, PLCs and freezers already produce the data. In most plants it is thrown away.
We put it to work: vision models that grade product at line speed, forecasting that tunes the tunnel, and alerts that reach a supervisor before a compressor takes the whole line down.
06 / Products
We don’t just advise on AI — we ship and run our own products. That is where our engineering comes from.
07 / The team
The people who scope your project are the people who build it. No junior bench, no account-manager telephone game — direct access to the engineers shipping your system.
08 / Questions
Most AI Labs projects reach production in 4–16 weeks, depending on scope. We start with a focused pilot, get it live, then iterate — rather than disappearing for months.
Start
Bring us a problem, not a spec. We’ll scope a pilot and get something real into production.
Start a project or talk to our team first