What is generative AI consulting?

Generative AI consulting helps businesses design, implement, and scale AI systems that generate content, automate workflows, and improve decision-making.

What are generative AI services?

Generative AI services include solution design, model integration, RAG implementation, fine-tuning, and deployment of AI systems for business use cases.

What does a generative AI company do?

A generative AI company builds and deploys AI-powered solutions such as chatbots, document automation tools, and intelligent assistants using large language models.

How do companies implement generative AI?

Companies implement generative AI by identifying use cases, preparing data, selecting models, integrating systems, and deploying AI workflows.

What is the process of generative AI adoption?

The process includes discovery, data preparation, model selection, development, deployment, and ongoing monitoring.

How long does it take to implement generative AI?

Implementation typically takes 2–8 weeks depending on complexity, data availability, and integration requirements.

What is RAG in generative AI?

RAG (Retrieval-Augmented Generation) is a method that combines large language models with external data sources to produce more accurate and up-to-date responses.

LLMOps is the practice of managing, deploying, monitoring, and optimizing large language models in production environments.

What models are used in generative AI solutions?

Common models include GPT, Claude, LLaMA, and other foundation models depending on the use case and infrastructure.

What are the main use cases of generative AI in business?

Key use cases include customer support automation, document processing, code generation, data analysis, and content creation.

How is generative AI used in enterprises?

Enterprises use generative AI to automate workflows, improve decision-making, enhance customer experience, and reduce operational costs.

Can generative AI automate business processes?

Yes, generative AI can automate tasks such as answering customer queries, summarizing documents, and generating reports.

Generative AI that ships to production

Generative AI consulting helps you find where AI pays off, then build it: content generation, workflow automation and better decisions, using LLMs, RAG and foundation models. We take you from use case to production, with governance and reporting in place.

Book a free meeting Start with an assessment

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AWS Premier Tier one of four clouds we build on

Weeks, not quarters Use case to working prototype

What is generative AI?

What is generative AI consulting?
Generative AI consulting helps businesses design, implement, and scale AI systems that generate content, automate workflows, and improve decision-making.
What are generative AI services?
Generative AI services include solution design, model integration, RAG implementation, fine-tuning, and deployment of AI systems for business use cases.
What does a generative AI company do?
A generative AI company builds and deploys AI-powered solutions such as chatbots, document automation tools, and intelligent assistants using large language models.

Everyone is adopting generative AI. Far fewer are getting value from it.

Adoption is no longer the hard part. The hard part is turning a working prototype into something that runs in production, meets your security and compliance rules, and shows up in the numbers. That is where most programmes stall.

We work in that gap: picking the use cases that pay off, building them on the cloud you already run, and putting governance and reporting in place so the result holds up.

Our generative AI services help businesses:

Automate repetitive and time-consuming workflows
Improve operational efficiency and reduce costs
Personalise customer engagement with AI
Speed up software delivery and engineering work
Improve internal knowledge management and decision support
Scale AI adoption across your cloud environments

88%

of organisations now use AI in at least one business function

39%

can point to any measurable EBIT impact from it

1 in 3

have scaled AI beyond pilots across the enterprise

5.5%

attribute more than 5% of EBIT to their AI use

Our generative AI services

We build generative AI on the cloud you already run — AWS, Azure, Google Cloud or Oracle — and take it all the way through to production.

Generative AI consulting and discovery
We work out which generative AI use cases are worth building, check whether your data and platform are ready, and prove the shortlist with a fast proof of concept.
- Use cases and business priorities evaluation
- Data quality and availability assessment
- Architecture and integration design
- Fast proof of concept validation
Read the case study
Generative AI development
We take a validated use case through to production: MVP, solution engineering, deployment on your cloud, and the training your team needs to run it.
- MVP development
- Solution engineering and deployment
- Scaling and integration
- Training and adoption support
Read the case study
Generative AI team augmentation
We add generative AI engineers and architects to your team, or review and optimise a solution you have already built.
- Augmenting engineering expertise
- Augmenting engineering capacity
- Consulting on all stages of development
- Solution audit and optimisation
Read the case study

Generative AI: the journey with us

Five phases from first workshop to a system your team runs without us.

GenAI Discovery Workshop

Rapid Prototyping and Validation

Solution Design and Prepare to Scale

Implementation and Empowerment

Ongoing Optimisation

GenAI Discovery Workshop

Goal

Find where generative AI brings the most return in your business, and confirm you are ready to build it.

Duration 1-6 workshops See the four-week assessment

What we do

Identify and qualify GenAI use cases
Define vision, priorities and success criteria
Assess readiness and data availability
Bring stakeholders up to speed on GenAI

Reference team

GenAI Engineer
Project Manager
Product Manager

Rapid Prototyping and Validation

Goal

Test the idea against real users and real data, so each step proves its value before you spend more.

Duration 2-8 weeks

What we do

Build a fast proof of concept
Validate with real users and real data
Refine the scope based on what comes back

Reference team

GenAI Engineer
Project Manager
Software Engineer
UX/UI Designer

Solution Design and Prepare to Scale

Goal

Set the architecture, roadmap and governance the solution needs to run in production.

Duration 2-4 weeks

What we do

Outline the implementation roadmap
Define the target architecture
Plan integrations and governance

Reference team

GenAI Engineer
Solution Architect
Business Analyst
Project Manager

Implementation and Empowerment

Goal

Build and deploy the solution so it is fully operational and your team can run it from day one.

Duration 2-4 months

What we do

Develop and integrate the validated solution
Deploy into your cloud environment
Train your team on the new technology

Reference team

GenAI Engineer
Solution Architect
Software Engineer
DevOps Engineer
QA Engineer

Ongoing Optimisation

Goal

Track how the solution performs in production and adapt it as your data, users and market change.

Duration On demand

What we do

Learn from real user feedback
Fine-tuning and prompt engineering
Monitoring and observability

Reference team

GenAI Engineer
Support Engineer
Project Manager

How is generative AI implemented?

How do companies implement generative AI?
Companies implement generative AI by identifying use cases, preparing data, selecting models, integrating systems, and deploying AI workflows.
What is the process of generative AI adoption?
The process includes discovery, data preparation, model selection, development, deployment, and ongoing monitoring.
How long does it take to implement generative AI?
Implementation typically takes 2–8 weeks depending on complexity, data availability, and integration requirements.

What technologies power generative AI solutions?

What is RAG in generative AI?
RAG (Retrieval-Augmented Generation) is a method that combines large language models with external data sources to produce more accurate and up-to-date responses.
What is LLMOps?
LLMOps is the practice of managing, deploying, monitoring, and optimizing large language models in production environments.
What models are used in generative AI solutions?
Common models include GPT, Claude, LLaMA, and other foundation models depending on the use case and infrastructure.

Generative AI for your industry

Healthcare

Your staff is overloaded with paperwork, between HIPAA rules and endless charts. Give your staff a helping hand by using AI to automate prior authorizations, flag abnormal lab results, and create discharge summaries, which will free up a lot of their time so they can focus on patient care.

Need tools specifically designed for your needs? Train models on your EHR data to triage high-risk cases or manage drug inventory. All hosted on HIPAA-ready servers with 24/7 monitoring, because patients are more important than IT problems.

Discover GenAI for healthcare

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Manufacturing

Tired of equipment failures? Generative AI can predict them before they happen. Train AI on your data to automate quality checks, reduce waste, and stay on schedule.

We connect AI to your sensors and systems, turning data into actionable insights. Focus on making great products, we’ll handle the tech stuff. No need for a PhD to get started!

Discover GenAI for manufacturing

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Financial

Fraud happens quickly. Your team can’t keep up. Our AI looks at transactions and finds suspicious activity without bothering your team with false positives. Automate your loan approvals, audit trails, and risk reports while following the rules.

Use your past transactions to teach our models to predict credit risks or create personalized client portfolios. We’ll keep your data safe on AWS/Azure, so you don’t have to worry.

Discover GenAI for financial services

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Retail

Tired of guessing what your customers want? Let AI do the hard work for you. By analyzing sales trends, weather patterns and what’s going on around the world, AI can predict demand with great accuracy. Automate your restocking process, send personalized promotions to your customers, and let your chatbots handle all the simple questions.

Connect AI to your POS and supplier systems to minimize your expenses and keep your shelves full. We’ll also make sure your system doesn’t crash on big shopping days like Black Friday.

Discover GenAI for retail

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Insurance

Insurance processes can be slow and complex. AI helps streamline underwriting, claims processing, and customer service by automating repetitive tasks and improving decision-making. Free your team from paperwork so they can focus on serving clients.

Train AI on your historical data to assess risks, personalize policies, and optimize operations. All hosted on secure, industry-compliant cloud platforms, so you can focus on protection, not IT management.

Discover GenAI for insurance

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Supply Chain

Generative AI is transforming the supply chain industry by enhancing logistics, reducing inefficiencies, and improving demand forecasting.

Companies leveraging AI-driven solutions gain a competitive edge by optimizing inventory, reducing costs, and ensuring seamless supply chain operations.

Discover GenAI for supply chain

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