AI integration

Add useful generative AI to the systems your teams already use.

Secure LLM features, retrieval, summarisation and content workflows integrated into existing products and operations.

Definition

Generative AI integration connects language or multimodal models to an existing application, data source or workflow. The work includes access controls, prompt and context design, evaluation, cost controls and user experience.

OpenAIAnthropicGeminiLlamaRAG
What changes

Outcomes shaped around the business.

01

Faster access to internal knowledge

02

Less manual drafting and summarisation

03

Features embedded in familiar workflows

04

Model choice without unnecessary platform lock-in

Delivery scope

A complete path, with clear boundaries.

Every engagement is scoped around the product and risk. These are the building blocks we commonly assemble.

  • Use-case and data assessment
  • LLM gateway and prompt architecture
  • Retrieval and citation layer
  • User interface integration
  • Quality, security and cost monitoring
Portfolio evidence
Seditio has integrated AI into pharmaceutical safety, B2B prospecting and talent-performance products with distinct data and workflow requirements.
Technology

Chosen to fit the workload—not the pitch deck.

OpenAIAnthropicGeminiLlamaRAGPostgreSQLVector databases
Common questions

Planning generative ai integration.

How does a generative ai integration engagement start?

We begin with a focused discovery workshop to understand the business case, users, constraints, existing systems and measures of success. The output is a practical scope, technical direction, delivery plan and decision log.

Can Seditio work with an existing internal team?

Yes. We can own delivery, augment an existing team or provide senior architecture and product leadership. Our Ireland and Philippines teams can overlap with client hours while also supporting continuous handovers across time zones.

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