For organisations where AI isn't paying off — yet When AI isn't paying off — yet

Most organisations are losing money on AI. We help you put AI only where it works.

Levantar helps you work out where AI will genuinely pay, prove it with evidence, and make it safe to rely on. Before you spend — or after you've spent and can't see the return.

The gap

88% are adopting AI.
Around 6% are getting real value.
Most organisations are stuck in the middle.

The difference isn't the model — it's placement, measurement and honesty about risk. That gap is why Levantar exists.

We help organisations be one of the few who get real value from AI.

AI adoption is racing ahead of returns. There's a gap in the market for a guide who has actually built and run these systems — and we work with executives, often technical, who are tired of the hype or have been burnt by it.

See what we offer

88%

of organisations are adopting AI

0100
39%

can attribute any profit impact to it

0100
~6%

are getting real value from it

0100

Real value = significant value from AI plus 5%+ EBIT impact attributable to it.

Source: McKinsey, State of AI 2025
How we measure this →

Closing that gap takes three things.

What we won't do

What we refuse matters
as much as what we offer.

We are not AI evangelists.

We know exactly how these systems fail, because we run them: drift, silent regressions, confident wrong answers, costs that grow faster than the value. We design for those failures from the first day rather than discovering them in yours. And if the evidence says don't build, we'll tell you.

We are not single-vendor sellers.

We don't sell one vendor's stack. We build and deploy adapter layers so applications use the right model for the right job at the right cost — cloud-hosted or local — and the measurement decides the tool, not a partner agreement.

What we do

Three ways in.
Start where the value is.

01

AI Value Diagnostics

Be confident AI is paying you back.

Most AI investment is committed before anyone can say what it will return.

We assess where AI will genuinely pay before you commit, and give an honest verdict on what you've already built — what to back, what to fix, what to stop funding. When the evidence says build, we guide your team through delivery, or build alongside you.

02

AI & LLM Security

Run AI you can trust.

AI systems fail in ways conventional security controls were never built to catch.

We assess the AI systems and LLM integrations you already run, and design new ones to be secure from the start. Either way you get the guardrails and evaluations that hold them in check, and the evidence trail — traces, evals, audit logs — that shows an auditor what your AI actually did, not what it was supposed to do.

03

Agentic AI

Put agents to work, safely.

An agent acting inside your business is a different proposition from a chat window answering questions about it.

We design agent systems rather than single bots: which use-cases are worth automating, how work passes between agents, and what has to be proven before any of it touches something real. And we connect them securely to your own data, wherever it lives — including the systems that were never built to be queried.

Track record

Organisations our founders have delivered for

Delivered personally by our founders across two decades of previous roles and engagements.

  • HMRC
  • DWP
  • Department for Transport
  • DEFRA
  • HSBC
  • First Direct
  • HP Enterprise
  • Equal Experts
  • AND Digital
  • Valtech
  • Zühlke
  • Intechnica
  • Capita
  • G2G3 Digital
  • PlusNet
  • On The Beach
  • LateRooms
  • EMIS
  • Assetz Capital
  • Split The Bills

We build and run AI products of our own — in production, with our own money at stake. That experience is what we bring.

Opptora, Upcast.Social, Tripwires and Secronyx — built, run and funded by us.

Meet the company
4 AI products in production
Daily Agents running in our own business
20+ years Delivering for the organisations above

Insights

Lessons from driving business value with AI.

Everything here comes out of something we built, run or delivered for a client — including the parts that went wrong.

Knowing who your agent is acting for, with AgentCore Identity

Validating the customer's token at the runtime, then having AgentCore Identity broker an on-behalf-of exchange for a five-minute, audience-restricted token that a second Cognito pool mints, built on…

Read the piece

AI-first, humans in control: a deeper, faster, wider CMS assessment

How Levantar helped Highfield, one of the UK's top five awarding organisations, decide the future of its content platform — working AI-first, with people owning every judgement.

Read the piece

Letting an agent run code, without letting it run loose

Giving an agent a managed Python sandbox with AgentCore Code Interpreter, putting a file in, running code over it, and seeing what the session can and cannot reach.

Read the piece

The pruning has started. Most of it is cutting the wrong branch.

AI budgets are being cut on cost because value is the harder number. What the 2026 cost-governance data shows, and what to prune on instead.

Read the piece

Giving your agent memory that survives the session

Adding AgentCore Memory to an agent so it keeps conversation events within a session and recalls extracted user preferences across sessions.

Read the piece

An agent at the centre

Six best-of-breed apps that don't talk, four small open-source MCP servers, and an agent in the middle. What we built, what broke, and what it taught us.

Read the piece

Contact

Talk to us before your next AI investment.

The first conversation is diagnostic, not a pitch.

Tell us which problem is yours — we'll come back with the relevant next step, not a deck.