AI Services
Generative AI Development
Custom generative AI — copilots, content engines and RAG applications built on the right models, grounded in your data and engineered to be safe and accurate in production.
- Copilots
- In-product & internal
- RAG
- Grounded on your data
- Private
- Your data stays yours
- Eval
- Quality proven
Overview
Generative AI, beyond the demo
Generative AI is easy to demo and hard to ship. The difference is the engineering around the model — retrieval, evaluation, guardrails, cost control and integration — that makes outputs accurate, safe and dependable.
We build production generative-AI systems: in-product copilots, document and content generation, summarisation and RAG applications, all grounded on your data with citations and tested before they reach users.
[1]In-product copilots
Assistants that guide users and surface the right action in context.
[2]Content generation
On-brand drafts, summaries and structured content at scale.
[3]RAG applications
Answers grounded on your knowledge base with verifiable sources.
[4]Search & discovery
Semantic search and Q&A over large, messy corpora.
[5]Coding assistants
Internal copilots that understand your codebase and standards.
[6]Safety & evaluation
Guardrails, red-teaming and automated evals before launch.
How we deliver
How we build generative AI
- 01
Define
Pick the use case and the metric that proves it works.
- 02
Ground
Connect your data with retrieval and citations.
- 03
Evaluate
Build evals and guardrails; red-team for safety.
- 04
Ship
Release with monitoring, cost controls and tracing.
Tools & technologies
The technologies we build with.
A pragmatic, best-of-breed stack — chosen for accuracy, cost, security and scale.
Why CodeGenIT
Generative AI done responsibly
Grounded
Retrieval and citations keep generation truthful.
Private
Your data isn't used to train third-party models.
Cost-aware
Routing and caching keep token costs predictable.
Evaluated
Automated evals make quality provable release to release.
Client voices
Trusted to deliver outcomes.
CodeGenIT turned a months-long AI ambition into a shipped, audited system our risk team actually trusts.
The new storefront is the fastest we've ever had — and conversion jumped the week we launched.
Proof
Outcomes we’ve shipped.
FAQ
Questions, answered.
Can’t find what you need? Our team is happy to talk specifics.
What is generative AI?+
Generative AI refers to AI models that create new content — text, code, images or structured data — from natural-language prompts. In software it powers chatbots, copilots, content generation and automation, typically built on large language models (LLMs).
How is generative AI different from a normal app feature?+
Outputs are probabilistic, so the engineering shifts to grounding, evaluation and guardrails to make them reliable and safe.
Will our data be exposed to model providers?+
No. We use private deployments and data agreements so your content isn't used to train third-party models.
How do you control cost?+
Model routing, caching, prompt optimisation and smaller models on cheap paths keep costs predictable.
Can you add a copilot to our existing product?+
Yes — we embed copilots into your app and data so they're useful in the user's real context.
Explore related
Ship generative AI users can trust
Let's turn a generative-AI idea into a dependable, measurable product.