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lloops. Practical AI solutions for your supply chainmaritimemarketing teams

We turn real business problems into working AI solutions your team can operate, improve and own.

Stage 01 · Curiosity call

Start with a curiosity call

We explore the problem, frame what matters and decide honestly whether a deeper engagement makes sense.

Stage 02 · AI immersion workshop

One day, your team, real problems

Up to ten people. We examine your problems through an AI lens, explore your data infrastructure and agree the outcome we're aiming for.

Stage 03 · Learning loops

Learning in loops

Prototypes, user feedback and fast iterations, in days rather than weeks or months. We build the context, architecture and governance that make AI stick. Capturing exceptions and building context on the go are part of the solution, not an afterthought.

Stage 04 · Confirmed outcome

Deployed, measured, owned

A working solution in operation, measured against the outcome we agreed at the start. Your team keeps the solution and the knowledge.

Ways to work together

AI initiatives stall between experimentation and operational ownership. Five ways to close that gap, with the approach, price and outcome agreed up front.

Curiosity Call & Advisory

Start here: explore the problem and the options. Focused advisory beyond that.

OutcomeClarity on the problem, the options and the next step
Book a curiosity call

AI Immersion Workshop

A one-day session for a team of up to ten people, built around your real problems and existing data foundations.

OutcomePrioritised opportunities and an empowered team
Plan a workshop

Working MVP

Business and IT together, from problem framing to end-to-end deployment.

OutcomeA working solution tied to a defined business outcome
Scope an MVP

Embedded AI Partner

An experienced AI partner alongside your team: knowledge base, architecture, delivery, capability.

OutcomeYour in-house AI expert, without the immediate hire
Discuss an engagement

Curated Context Graphs

Keep the judgement behind corrections, overrides and exceptions so your AI learns how your organisation really works.

OutcomeAn owned memory of decisions, reasons and evolving business rules
Learn about context graphs

Why lloops

The engagement model is designed so the value stays inside your organisation after the engagement ends.

Learning loops

Every exception your team resolves becomes a reviewed rule. The brain compounds.

Local loops

Deployed once in your infrastructure. Owned by you. Not another SaaS.

Live loops

Not just static software. The brain runs with the team every day, updated with every decision.

Outcome-driven

Every engagement is built around a defined business problem and a measurable result.

Working software

Prototypes and end-to-end deployment, not slideware, with business and IT at the table from day one.

Your context stays yours

A knowledge base keeps organisational context in-house, with your team.

No lock-in

Model- and framework-agnostic, with transparent one-time or outcome-linked fees. No recurring SaaS dependency.

Capability transfer

The engagement leaves behind an in-house AI expert or team, not a dependency on lloops.

Who you'll work with

About Urvesh

I am Urvesh Devani, an AI and technology leader. I have spent 12 years building software, data and AI products, the last 7 of them in global supply chains and shipping.

Most recently I was VP of Technology at Portcast, where I led a fifteen-person team and shipped AI products used by Fortune 500 shippers. The latest was a freight audit product that made invoice checking about ten times faster and saved shippers roughly 20% more in costs.

The technology is rarely the hard part. The real work is picking a problem that is actually worth solving, then building something your team trusts and uses every day.

What makes AI genuinely useful in a business is everything your team already knows: how decisions really get made, which exceptions matter, why the obvious answer is sometimes wrong. My job is to capture that knowledge in a system you own, running in your own infrastructure, so it keeps getting smarter with your team long after my work is done.

Book a curiosity call

A focused conversation to explore the problem, identify options and decide the next step together. The curiosity call costs $0.

Tell me about your use case

A few lines so the call starts prepared. Your details carry straight into the booking, nothing to type twice.

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