LLM Integration
Add language-model features to your existing product.
Start Your ProjectWe integrate LLMs into your application, summarization, extraction, classification, generation, with the right model choice, prompt engineering, cost controls, and fallbacks for production reliability.
- Use-case and model selection
- Prompt engineering
- API integration
- Cost and rate management
- Caching and fallbacks
- Output validation
You have an existing product and a clear place an LLM would help, summarizing, extracting, classifying, generating, and you want it added properly rather than bolted on with a raw API call and crossed fingers. The gap between a prompt that works in a playground and a feature that is reliable, affordable, and safe in production is where this lives. If AI is a feature inside your app, not the whole product, integrating it with cost controls and fallbacks is what makes it dependable.
How We Approach It
Match model to use case
We benchmark options on your actual task against latency and cost, rather than defaulting to one provider, and pick what fits.
Engineer the prompts
Prompt design and output structure tuned for your use case, so results are consistent enough to build a feature on.
Control cost and rate
Caching, rate limits, and prompt efficiency so spend stays predictable as usage grows, not a surprise bill.
Add reliability
Fallbacks and output validation so a slow or bad model response degrades gracefully instead of breaking your app.
The Difference It Makes
Right Model
Chosen for your task and budget.
Cost-Controlled
Caching and limits keep spend predictable.
Reliable
Fallbacks and validation for production use.
Fast to Add
Ship AI features into your existing app.
Technologies We Use
Common Questions
Which LLM should we use?
How do you control LLM costs?
Related Services
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