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Practical AI

From AI experiments to tangible business value

Amplifi helps organizations move from AI interest and experimentation to practical, governed solutions that create measurable business value.

We help you identify where AI can deliver value, choose an approach that fits your existing technology investments, build trusted foundations, and move into execution without turning AI into an open-ended transformation program.

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Recognized by Gartner®

Market Guide for AI and Data & Analytics Services Providers

6-12 weeks

Amplifi AI Accelerators deliver measurable outcomes at speed

a critical capability

Why practical generative and agentic AI matters now

Organizations are adopting AI faster than their operating models, data foundations and governance can mature.

Tools such as Claude, ChatGPT, Copilot and platform-native AI capabilities are already in use across most organizations, what’s now lagging is everything that makes them trustworthy at scale. Businesses need to start from a clear understanding of where AI can deliver value, an approach that fits existing technology investments, and the data foundations and governance to support it.

Practical AI is about moving from AI interest and experimentation to governed solutions that create measurable business value, and getting into execution without turning AI into an open-ended transformation program.

According to Gartner®, only 17% of organizations have deployed AI agents, yet over 60% expect to within two years.

Meaning before models.

Inconsistent AI answers are rarely a model problem… they happen when the business hasn't agreed what its metrics, entities and definitions actually mean.

Business challenges

Do any of these sound familiar?

Teams are experimenting with AI, but leadership lacks a defensible view of which use cases should be funded, piloted or scaled.

The market is changing quickly and leaders need help comparing models, copilots, agentic platforms and native capabilities against their architecture, governance requirements and existing investments.

Natural-language analytics and agents can produce inconsistent answers when metrics, entities, relationships and business definitions are fragmented across warehouses, BI tools and tribal knowledge.

Organizations lack visibility into answer quality, agent behavior, usage patterns and spend, making it hard to scale adoption confidently or understand why capacity and budgets are being consumed.

our clients

Which leading brands have trusted Amplifi with their data and AI?

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6 expert tips for driving business value with AI

Unlock real business value from generative AI with six expert strategies that help organizations build strong data foundations, improve decision-making, and drive measurable outcomes with confidence.

our approach

A bounded, outcome-led approach

We start with the business problem and work toward measurable delivery. Across the portfolio, the pattern is to align leaders, identify the highest-value opportunities, make fit-for-purpose platform decisions, ground AI in governed business meaning, implement a focused solution, and then evaluate and operate it over time.

Where scope permits, we move beyond recommendations: offerings such as AI Accelerators and Spend Optimization implement agreed changes and leave you with an operating process, not only a strategy deck.

01

Start with business outcomes, not technology

Opportunity Discovery begins with corporate initiatives, strategic priorities, pain points and measurable value before defining a solution.

02

Start narrow and prove value

For semantic work, we recommend a focused first slice rather than an enterprise-wide ontology; for implementation, AI Accelerators target measurable outcomes in approximately 6–12 weeks.

03

Use your native ecosystem where it makes sense

Semantic definitions and AI capabilities are projected into the platforms you already use rather than forcing a replacement architecture.

04

Make evaluation part of delivery

Representative questions, expected behavior, failure classification and regression testing establish confidence in analytics and agent responses.

Featured Case studies

Products needing classification

30,000

Complex product data categories across 30,000 SKUs

4 level-heirachy

Troy: Building AI and ML product classification capabilities to boost operational efficiency

Amplifi helped Troy streamline their product classification process using AI and machine learning, reducing manual input and improving accuracy, while also laying the foundation for future AI-driven innovation.

Why work with us

How can Amplifi help you get practical with AI?

Our Practical Generative & Agentic AI services span executive advisory, opportunity discovery, platform and tooling selection, semantic grounding, focused implementation accelerators, evaluation and AI spend optimization. We work with organizations that have real business objectives and existing technology investments, but need help translating rapidly changing AI capabilities into a focused plan and executable solution.

Advisory and delivery, one team

Our approach combines practical AI advisory with hands-on data, analytics and implementation expertise. The people who help you prioritize and plan are the same people who build, so recommendations turn into working solutions rather than a strategy deck.

Trusted by data and technology leaders

We work with CIOs, CDAOs, CTOs, analytics and data leaders, digital transformation leaders and business executives who need AI to move from experimentation to measurable business value.

Built on your existing platforms

We work in environments built around Snowflake, Databricks, Microsoft Fabric, Power BI and other enterprise data platforms, projecting AI capabilities into the ecosystem you already run rather than forcing a replacement architecture.

Tailored to your starting point

Every engagement is shaped around your business priorities, AI maturity, governance requirements and platform landscape, whether you need to prioritize AI investments, establish trusted data and semantic foundations, deliver a pilot, or improve the cost and manageability of an existing AI environment.

"Amplifi have been a reliable and supportive partner to Troy throughout our data journey, providing insight into the industry, helping us identify the correct path and enabling our data to unlock value across the Group."

Gareth Thomas Chief Data & Technology Officer at Troy

insights

Further reading

News
Amplifi launches Axis, an AI-driven service to unlock value from unstructured and legacy data Discover Amplifi Axis, a new AI-driven service that transforms unstructured and legacy data into structured, reusable data products, helping organisations unlock value and scale data and AI use cases.

FAQs

You ask, we answer.

The questions we hear most from data and AI leaders, and how we approach them.

Individual tools are a start. Business value comes from AI grounded in your enterprise data and business definitions, governed, evaluated and embedded in workflows. That’s a different challenge from rolling out licenses.

Making sure AI understands what your metrics, entities, relationships and business definitions actually mean, so natural-language analytics and agents give consistent answers rather than confident guesses.

AI that doesn’t just answer but acts: reasoning through a task, calling systems and completing steps within defined guardrails. Valuable when governed and evaluated; risky when not.

An AI Landscape Session takes 60–90 minutes. Opportunity Discovery lands in hours or weeks depending on scope. AI Accelerators deliver measurable outcomes in approximately 6–12 weeks; Axis for delivering structure to unstructured data can be within in 3–8, depending on volume.

Not all of it. We start with the data and business meaning behind your first use case, and work alongside our Trusted Data Foundations practice where deeper work is needed.

Visibility first: usage patterns, answer quality and where capacity is being consumed. Our Spend Optimization work then implements the agreed changes so you’re left with an operating process.

Let's start a conversation about data.

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