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metabytes
ABOUT METABYTES

We help businesses put AI to work.

Metabytes helps organisations find where AI creates value, redesign the work around it and build the systems that make it run in production.

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What Metabytes is

AI transformation and engineering, from opportunity to production.

We combine strategy and engineering in one team, so the work that gets prioritised is the work that gets built, governed and run.

  1. 01  OPPORTUNITY

    Strategy

    Find where AI can create value and decide what should happen first.

    OPPORTUNITYWORKFLOWVALUEPRIORITY
  2. 02  DESIGN

    Agents & automation

    Redesign the work around AI, automation, people and controls.

    AGENTAUTOMATIONHUMAN REVIEWCONTROL
  3. 03  BUILD

    Software & knowledge

    Build the software, knowledge and data layer around the workflow.

    SOFTWAREKNOWLEDGERETRIEVALINTEGRATION
  4. 04  RUN

    Platforms & governance

    Put the system into production with the infrastructure, governance and visibility it needs.

    PLATFORMGOVERNANCEEVALUATIONOPERATIONS
    PRODUCTION SYSTEM
ONE TEAMONE DELIVERY PATH
From first priority to live system, without a handover.
See how we work→
Why Metabytes exists

AI creates value when it changes how work gets done.

Most organisations have tried AI. Far fewer have changed a real workflow with it. The difference is the system around the model: process, data, tools, controls and people.

THE MODEL IS ONLY ONE PART

Value comes from the workflow around it.

PROCESSDATAMODELTOOLSCONTROLSPEOPLE
1 OF 6 PARTS. METABYTES DESIGNS ALL SIX.Explore our AI stack→
What we believe

Five principles shape how we design AI systems.

These principles guide the decisions we make across strategy, architecture, delivery and production. They keep AI systems useful, replaceable, controlled and measurable.

DESIGN PRINCIPLE

Start with the work. Build only what the system needs. Measure what happens in production.

PRINCIPLE 01 OF 5. APPLIED TO EVERY BUILD.See how we work→
Production
AIUSEFULCONTROLLEDMEASURABLE
PRINCIPLE 01

Start with the work

The first question is what work needs to improve, what outcome matters and what currently gets in the way.

TRIGGERCONTEXTDECISIONACTION

  • The first question is what work needs to improve, what outcome matters and what currently gets in the way.

    TRIGGERCONTEXTDECISIONACTION
Production AIUSEFUL, CONTROLLED, MEASURABLE
Strategy + engineering

Strategy decides what matters. Engineering makes it real.

Strategy without engineering stops at the roadmap. Engineering without strategy risks building the wrong thing.

Metabytes brings both disciplines into one team, so priorities move directly into systems that can be built, governed and run.

What gets prioritised is what gets built.

SAME PEOPLENO HANDOVERONE BACKLOG
How AI should work

The model is only one layer of a useful AI system.

Useful AI connects workflow, context, tools and controls. Once live, it is evaluated and observed.

Model-agnostic approach

The architecture should fit the workload, not the vendor.

Hover a workload to see an illustrative route. We work across commercial and open models and choose by evaluation.

Workload
Router
MODEL ROUTER
Models
OpenAIFALLBACK
ClaudeROUTED
Gemini
Grok
Open models
Output
Agent
App
Search
Workflow
Why this route
Reasoning → AI Router → Claude → Agent
  • TaskMulti-step reasoning
  • ContextLong, mixed sources
  • LatencyTolerant
  • PolicyStandard data
  • FallbackSecondary frontier model
Compare AI models→
From opportunity to production

From AI opportunity to production system.

We move from identifying the right work to designing, building, proving and operating the system in production.

DISCOVERDESIGNBUILDEVALUATEOPERATE
AFTER LAUNCHLIVE

The work does not end at launch. Production AI is measured, operated and improved over time.

MONITOREVALUATEIMPROVEREDEPLOY
ACTIVE PHASE 01

Discover

Find where AI can change the work.

What we build

AI systems that do useful work inside real businesses.

We build the agents, automation, software, knowledge systems, platforms and controls needed to make AI useful in real workflows. Each can stand alone, but the strongest systems combine several.

BUILT AS A SYSTEM
AGENTSDATASOFTWARECONTROLS

Agents, data, software and controls work better when they are designed together.

Explore all AI services→
AI systemAGENTS + AUTOMATION + KNOWLEDGE + GOVERNANCE
AI systemAGENTS + AUTOMATION + KNOWLEDGE + GOVERNANCE

AI agents

01 OF 06
TASKPLANTOOLACTION
OFTEN COMBINED WITHKNOWLEDGETOOLSGOVERNANCE
How we work with clients

An extension of your team, not a black box.

Shared ownership, transparent decisions and a practical handover keep capability inside your business.

SHARED OWNERSHIPVISIBLE DELIVERYPRACTICAL HANDOVER
OWNERSHIP OVER TIMECapability moves to you
BUILD
METABYTES
EMBED
METABYTESYOUR TEAM
HANDOVER
YOUR TEAM
Indicative split. The pace depends on your team and the system.
See how we deliver→
  • 01

    Transparent

    Architecture, prompts and evaluations are visible to your team.

    VISIBLE DECISIONS
  • 02

    Collaborative

    Your domain experts help shape workflows, controls and priorities.

    SHARED WORKFLOW DESIGN
  • ONE TEAMPlan together. Build visibly. Hand over clearly.
  • 03

    Progressive

    We build first, then hand over more ownership as your internal capability grows.

    CAPABILITY TRANSFER
  • 04

    Accountable

    Each system has named owners, operating rules and success measures.

    NAMED OWNERSHIP
Trust, governance & evaluation

AI systems need visible control.

Every important AI action should have clear inputs, permissions, policy checks, ownership and evidence. We design those controls into the workflow from the start.

That means teams can see what the system used, what it did, who approved it and how the outcome was evaluated.

  • PERMISSIONEDAI only sees and uses what it is allowed to access.
  • CONTROLLEDSensitive actions can require checks, approval or escalation.
  • TRACEABLEInputs, decisions, actions and evaluation remain visible.
Explore AI Governance & Security →
CONTROLLED AI ACTION
WORK
REQUESTCONTEXTMODELTOOL
SOURCESused as context
CONTROL GATEACTION WAITS HERE
PERMISSIONSCOPED ACCESS
POLICYRULES APPLIED
APPROVALREQUIRED FOR WRITE ACTION
ACTIONEVALUATE
ACTION TRACE
SOURCES LOGGEDTOOL CALLEDPOLICY PASSEDAPPROVEDEVAL PASSEDOWNER NAMED

Every action passes through the control gate before it runs.

Selected work

See the process in working systems.

Customer service agentAll seven phases, from workflow map to monitored production.UnderstandBuildDeployView project →Multi-model workflow routerHow the Build and Improve phases stay model-agnostic.DesignBuildImproveView project →Document intelligence pipelineExtracting, validating and routing documents with human review.PrioritiseBuildEvaluateView project →Governed knowledge assistantPermissioned retrieval with citations, evaluation and audit.DesignEvaluateDeployView project →
Who we work with

Different stages need different AI systems.

We adjust the architecture, controls and delivery model to match the size, complexity and maturity of the organisation.

WHAT CHANGES AS YOU GROWSTAGE 01 OF 03
COMPLEXITYLOW
CONTROLLIGHT
INTEGRATIONFEW

Start with what the organisation needs now. Add complexity only when the work demands it.

AI MATURITY MAP
  1. 01

    Small business

    START SIMPLE

    Practical automation, assistants and integrations without unnecessary platform complexity.

    WORKFLOWAUTOMATIONOUTCOME
    FASTER WORK
  2. 02

    Mid-market

    CONNECT THE WORK
    CONNECTED WORKFLOWS
  3. 03

    Enterprise

    SCALE WITH CONTROL
    CONTROLLED SCALE
From the CEO

Change the work, not just the tools.

Liam Derbyshire, CEO of Metabytes
LIAM DERBYSHIRECEO
FOUNDER NOTE

Start with the work. Then decide where AI belongs.

Liam DerbyshireCEO, MetabytesSTRATEGY + ENGINEERING + DELIVERY
  1. 01Starts with the workflowWe look at the work first, then where AI fits.
  2. 02Built for productionStrategy, engineering and controls are designed together.
  3. 03Designed for ownershipSystems are transparent, governable and built to hand over.
Our principles

Principles for AI that survives production.

These principles guide how we choose architecture, design controls and judge whether an AI system is actually working.

BEFORE WE BUILD, WE ASK3 QUESTIONS
  1. 01 · ARCHITECTURE

    Stay model agnostic

    Use the architecture that fits the workload.

    Build for change

    Models, prices and capabilities will continue to move.

    WORKLOADROUTER
    MODEL AMODEL BMODEL C
    Provider can change without rebuilding the application.
  2. 02 · HUMAN CONTROL

    Prefer useful over impressive

    A simple automation that works is better than an unnecessary agent.

    Keep people where judgement matters

    Design approval and escalation deliberately.

  3. 03 · PRODUCTION

    Make the system observable

    Production AI needs evaluation and visibility.

    Measure business work

    Judge AI by the task and outcome it improves.