Logistics is entering
its AI era.
Most executives know AI matters. The hard part is knowing where and how to apply it.
That is the work we do. Discover the art of the possible.
- AI billing automation
- Warehouse systems (WMS)
- AI training
- Operational automation
- Data & systems integration
An AI consulting-led company for logistics.
We handle training, strategy and implementation. The work starts with the problem, not the technology, and it ends wherever you want it to.
What we build
AI software and technology solutions for logistics and supply chain businesses. And we implement them, inside the operation, alongside the systems you already run.
How we start
By understanding the problem. That means AI training for your teams, or a structured assessment that finds where AI creates real return, and in what order.
How we implement
We are not tied to one answer. We select off-the-shelf systems, extend the systems you already run, or build new. Whichever fits the problem best.
How far we go
Your decision. Some clients take the strategy and build with their own teams. Others ask us to deliver it, or to supervise the build. We stay flexible.
Most of the pain sits in the gaps between systems.
Six patterns we see across large logistics businesses. We have dealt with every one of them inside live operations.
Systems that do not talk
Middleware breaks, and data is rekeyed by hand between systems that were never designed to work together. Every new connection becomes a project of its own.
Numbers that arrive too late
Performance becomes visible weeks after the month it describes, because every number is a small project. Decisions rest on instinct, or on last month’s view.
Commercial terms that live in email
Rates are agreed and revised in conversation, but never held anywhere an invoice can be built from. So billing runs late, wrong, or both.
Core systems that are hard to change
The products are capable but only partly implemented. Every change carries a vendor backlog, and spreadsheets run alongside to fill the gaps.
Post-merger estates that take years to converge
Acquired companies arrive with their own systems, data models and commercial formats. Meanwhile, the operation still has to run and bill every day.
AI that is sponsored but not used
Leadership backs it, but teams drop it once the pilot ends. The investment stalls at the demo stage, and the tools never reach daily work.
You can start small. We guide you where to start.
We teach your people
Executive, team and department programmes, from the boardroom to the operations floor.
- Delivered personally by Denis and Pavan.
- People leave using AI daily, on their own work.
We find where AI pays off
A scored assessment across the operation, or a short discovery on one named problem.
- Findings ranked by return and effort.
- Every recommendation carries an expected return.
We build it into your operation
Solution-agnostic: extend what runs, connect what does not talk, and implement new only where genuinely needed.
- Buy, configure or build, and we will say which.
- Modular and API-first, so it moves with your systems.
Running inside live logistics operations.
Examples of work already built and running inside live logistics operations, with the results the operators report.
Billing automation87%Reduction in overdue receivablesRate cards became formulas. Overdue receivables fell 87%
A logistics operator was invoicing late and wrong because rate cards lived in documents, revisions lived in inboxes, and billing waited on vendor invoices. Digitising the terms, connecting them to where changes happen, and billing from operational data cut overdue receivables by 87%.
Read case study
Workflow automation3xCustomer volume the same team handlesSame team, three times the customer volume
Skilled people at a logistics operator spent most of their day on administration: retyping documents, chasing approvals and answering the same questions. Agents built around those workflows took the busy work, and the client reported the same team handling three times the customer volume.
Read case study
Rapid implementation6 weeksFrom start to a full system runningA full system stood up in six weeks, not a capital programme
System implementations in logistics take longer and cost more than planned because requirements are collected in workshops, selection is guesswork, and migration is underestimated. With AI doing the analysis, testing and configuration, one client stood up a full system in six weeks.
Read case study
AI training3Programme tracksExecutives who build their own tools. Teams that use AI on their own work
Every logistics organisation is working out how to adopt AI, and generic courses teach the tools rather than how to think. We run programmes where executives build small customised solutions on their own machine, finance uses AI for finance work, and operations teams solve floor problems themselves.
Read case study
More of what we build
- Operational email automationOperational inboxes read, classified and drafted by AI. The team reviews instead of typing
- CRMA CRM the sales team actually keeps current
- MiddlewareNew partner integrations in days, not projects
- Compliance automationAudit-ready all year, not once a year
- Warehouse system augmentationActivity captured is activity billed
- Carrier EngineOne connection for customers and partners. The right carrier and rate on every parcel
We agree on a start point: a specific problem, the full picture, or your people.
We plug into any stage of your AI journey. Start anywhere, hand off anytime, with no forced end-to-end commitment. We pick up where others left off, and hand over internally or externally whenever you are ready.
- 01
Training
A custom executive, team or department programme.
You leave with
People who use AI, and usually a small working tool.
- 02
Assessment
A scored review across eight dimensions.
You leave with
A heatmap and, at depth, a ranked roadmap.
- 03
Discovery
A scoped problem becomes a defined project.
You leave with
A proposal with the expected return attached.
- 04
Selection
When a new system is the right answer.
You leave with
Buy, configure or build, and we will say which.
- 05
Implementation
Proof of concept, MVP, production.
You leave with
A working system inside the operation. It stays yours.
Start with your people
You want leadership and the team to see and use AI first. Learn and showcase the opportunity with executive stakeholders and the team. Start today.
You get
Leaders using AI on their own work, and a view of where to take it.
Start from the full picture
Find where the biggest problems are. You are not sure where to start, so we look at the whole picture, tell you where to begin, and build a roadmap.
You get
A heatmap, and a roadmap ranked by payoff.
Start from a problem
Name the most pressing problem you have today. You are clear on the problem area, and we can get started and tackle it right away.
You get
A scoped project, with the expected return attached.
A working session to define the scope: which entry point, and what to point it at.
Experts and operators, working with the people who lead the business.
Every programme and every build is delivered personally by the two founders.
Denis Konoplev
CEO & Co-Founder
Four companies founded, two valued above USD 100m. Enterprise and government AI programmes since 2015.
- Founded a computer-vision company out of LSE research, since acquired.
- Entrepreneur in Residence at the Dubai Future Foundation accelerator.
- Leads AI training and tooling for executives across the RSA Global group.
Pavan Kumar T V
CTO & Co-Founder
25 years building and running technology organisations, from startups to 100-plus engineering teams.
- Machine learning in production since 2012, from forecasting to computer vision.
- Co-founded two startups. Led a 100-strong engineering team through an acquisition.
- Technical due diligence for investors, and advisor to venture studios in the region.
Discover the art of the possible.
Bring the problem that costs you most, or bring the whole picture. We will tell you where to start, and what it should return.