Redesign how the business works.

At a glance

Headline: From scattered pilots to one working system.

Many businesses have AI experiments. Far fewer have a clear operating model for turning them into repeatable value. Tangible Labs helps leadership teams decide where AI matters, sequence the change and build the systems needed to put it into operation.

At a glance

• Business first: Begin with the outcome, not a predetermined model or platform.
• End to end: Connect strategy, workflows, architecture, implementation and adoption.
• Built for reality: Design around existing teams, data, controls and systems.
• Measurable: Define evidence of value before scaling investment.

What can be transformed

Strategy and investment

Choose the right AI opportunities, build the business case and establish clear decision criteria.

Functions and workflows

Redesign sales, service and internal operations around effective human and AI collaboration.

Platforms and architecture

Create the data, integration and AI foundations required for secure, scalable delivery.

Adoption and governance

Equip teams, define ownership and establish controls that let AI move safely into daily work.

Transformation services

1. AI Transformation Strategy

Define where AI can create value and which opportunities deserve investment.

1. AI Roadmap

Turn ambition into a phased plan of pilots, platforms, capabilities and milestones.

1. Operating Model and Workflow Redesign

Rebuild roles, decisions and workflows around people and AI agents.

1. Sales Transformation

Connect AI agents, automation, data and CRM around a stronger sales system.

1. Customer Service Transformation

Redesign service across voice, messaging, self-service, agents and human escalation.

1. Legacy Modernisation

Make established systems AI-ready without assuming that everything must be replaced.

1. Enterprise AI Adoption and Change

Move AI from isolated pilots into governed, repeatable use across teams.

1. Data and AI Architecture

Design the secure technical foundation for agents, RAG, automation and analytics.

What this changes for you

• A shared AI direction linked to business priorities
• Fewer disconnected experiments and duplicated investments
• Clear choices about what to build, buy, integrate or stop
• Redesigned workflows with explicit human and AI responsibilities
• Stronger foundations for data, integration, security and governance
• A practical path from first proof to wider adoption

What we deliver

• Current-state and AI-readiness assessment
• Prioritised opportunity portfolio
• Business cases and value hypotheses
• Target operating model and workflow designs
• Data, application and AI architecture
• Pilot and implementation roadmap
• Adoption, governance and measurement framework
• Working products, automations and integrations where delivery is in scope

How we work

1. Frame the outcome

Align on the business movement required, the users affected and the constraints that matter.

1. Map the system

Examine workflows, decisions, data, technology, roles and points of friction.

1. Design the future state

Define the operating model, target architecture and highest-value interventions.

1. Prove the critical assumptions

Test value, feasibility, user behaviour and risk through focused proofs.

1. Build and embed

Deliver in working releases, connect existing systems and prepare teams to use them.

1. Measure and expand

Evaluate verified outcomes, improve the system and scale only what works.