AI & automation
LLM integration
Language models added to an existing product or internal tool, with structured output.
What is LLM integration?
LLM integration means adding a large language model, the technology behind tools like ChatGPT, inside your own product or internal tool, so it can draft, summarise, classify or extract information as part of the workflow. The output is structured and checked, so the rest of your software can rely on it.
What problem does LLM integration solve?
Pasting prompts into a chat window works for one person on one task. Inside a product it doesn’t: answers come back in a different shape each time, costs grow with every user, and nobody knows how often the output is wrong.
A proper integration defines exactly what the feature must produce, constrains the model to that format, controls cost and tests the results, so the AI behaves like any other dependable part of your software.
What you get
AI features inside your product that return structured, predictable output and fit the rest of the application.
LLM integration
What’s included
Feature design
Exactly what the feature must produce, and how success will be measured.
Model selection
The model chosen to suit the task, the data involved and the cost.
Structured output
Prompts and formats that return predictable results your software can use.
Cost and usage controls
Limits and caching that keep costs predictable as use grows.
Evaluation
Tested against real examples before launch, and after every significant change.
Monitoring
Usage, cost and failures tracked once it’s live.
Who LLM integration suits
A good fit for
- Software products adding AI features. Summaries, drafts or suggestions inside your app.
- Internal tools that draft or summarise. First drafts of quotes, reports or replies for staff to check.
- Platforms generating structured documents. Turning messy input into consistent, usable records.
Probably not the right fit if
- Your team just needs help drafting emails. A general AI subscription is cheaper.
- The feature must be right every single time with no review. Keep a person in the loop.
- There’s no product or tool to add it to yet. Start with the workflow.
How it works
How it works
- 01
Define the output
Exactly what the feature must produce, and how it will be checked.
- 02
Build and constrain
Structured output that the rest of the product can rely on.
- 03
Evaluate
Tested against real examples before and after launch.
How long does LLM integration take?
A focused AI feature is usually a 4–6 week build, including the accuracy testing. Adding it to an existing product depends on how that product is built, and we confirm the timeline in your fixed quote after looking at it.
How much does LLM integration cost?
AI features are quoted on the task, the data involved and the expected volume, plus AI usage that we estimate before you commit. You get a fixed quote after a free 30-minute call, before any work starts.
Related work
Built and in production.
Questions
About LLM integration
Which AI models do you use?
We choose the model to suit the task, the data involved and the cost, and can change it later without rebuilding the feature.
Can AI features keep their costs under control?
Yes. Usage limits and caching keep costs predictable as use grows, and we estimate running costs before you commit.
Can you add AI to software we already have?
Yes. Most products can take an AI feature through their API or database, without being rebuilt.
How do you stop the model returning nonsense?
The output is constrained to a defined structure and checked before the rest of the product uses it. Anything that fails the checks is rejected or sent for review.
What happens to the data we send the model?
We choose providers and settings to suit the data involved, limit what the model can access and keep sensitive information out of prompts where it isn’t needed.
Further reading
AI & automation
More in AI & automation
- AI assistantsAssistants for customers or staff that answer from your own content and hand over to a person.
- Document search & retrievalAsk questions across your documents and get answers that cite the source.
- Workflow automationRemove repetitive steps: sorting enquiries, extracting details and updating systems.
- Evaluation & guardrailsTest sets, output checks and limits, so you know how accurate the AI is.
- All of AI & automationThe full service, related work and questions.
Enquire
Talk to us about LLM integration.
Tell us what you are working on and what you need. An outline is enough to start. We reply within one business day.
Prefer email? hello@vareonhq.com