Generative AI
AI models that generate text, code or other content, integrated into products and workflows where they create genuine value.
What it enables
- Text generation for drafting, summarizing and content assistance
- Conversational assistants embedded into products or internal tools
- Automated content and code generation for repetitive, well-defined tasks
Why it matters for your project
- Generative AI applied to real workflows, not added for its own sake
- Time saved on drafting, summarizing and repetitive content tasks
- New product features that weren't practical to build before generative models existed
Generative AI services
AI Assistant Development
Conversational assistants built into products or internal tools, scoped to specific, well-defined use cases.
Content & Workflow Automation
Generative AI applied to drafting, summarizing or transforming content as part of an existing workflow.
LLM Integration
Integrating large language model APIs into existing products, including grounding responses in your own data where accuracy matters.
How we work with Generative AI
Use cases scoped narrowly at first, so value is provable before wider rollout
Prompting and grounding treated as engineering work — tested and version-controlled, not guesswork
Edge cases and failure modes tested deliberately, not just the expected inputs
Frequently asked questions
Common areas include drafting and summarization, customer-facing assistants, and automating repetitive content or data-transformation tasks. We assess your specific case before recommending it.
It varies by use case. Where accuracy matters, we ground responses in your own documents and data through retrieval-augmented generation, and test edge cases carefully.
Yes, this is one of the most common ways we integrate generative AI, through APIs added into an existing product rather than a rebuild.
Part of our AI Technologies stack
Building something with Generative AI?
Tell us about the project and we'll help you figure out the right technical approach.