AI & LLM Integration
Practical AI inside the software you already use.
We build AI features that do useful work: assistants that answer from your own documents, automated extraction and classification, and AI steps inside existing workflows, using models such as GPT, Claude and Gemini, with evaluation and safeguards built in.
KPIs we move
- Answer accuracy
- Time saved per task
- Cost per request
What’s included
Everything ai & llm integration needs.
Assistants on your knowledge
Chat and search that answer from your documents, policies and data, with links to the sources used (retrieval-augmented generation).
Document extraction
Read invoices, forms, contracts and emails, pull out structured fields, and route them to the right system.
Workflow automation
AI steps inside existing processes: triage tickets, draft replies, summarise calls, enrich CRM records.
Model selection
The right model for each job across OpenAI, Anthropic, Google and open models, balancing quality, speed and cost.
Evaluation and guardrails
Test sets that measure accuracy before launch, plus defences against prompt injection and leaks of sensitive data.
Cost and usage control
Caching, smaller models where they suffice, and usage limits, so running costs are predictable.
Why it matters
Outcomes, not activity.
Evaluated, not guessed
Measured before launch
Every AI feature is tested against real examples, so you know how often it is right before customers see it.
Privacy by design
Your data stays yours
We use providers and settings that do not train on your data, and keep sensitive fields out of prompts where possible.
Task-first scoping
Useful, not a demo
We start from a task that costs your team time today and build until it measurably takes less.
Our process
How we deliver it.
Pick the task
Choose one task where AI can save real time, and collect real examples of it.
Prototype and evaluate
A working prototype scored against those examples, with costs estimated per request.
Integrate and harden
Connect to your systems, add guardrails, logging and human review where needed.
Launch and monitor
Release gradually, track quality and cost in production, and improve with feedback.
Tools & platforms we use
Deliverables
What you’ll get.
- Use-case and data review
- Evaluation test set
- Working prototype
- Production integration
- Guardrails and monitoring
- Cost estimate and controls
FAQs
AI & LLM Integration questions.
Guides
Read before you decide.
How to choose a tech stack for a SaaS product
A practical way to choose languages, frameworks, databases and hosting for a SaaS MVP without painting yourself into a corner.
SaaS · 3 min readWhat does it cost to build a SaaS MVP?
What drives the cost of a SaaS MVP, how to estimate it yourself before asking for quotes, and where founders overspend.
Strategy · 3 min readHow to choose a software development company
The questions that separate a reliable software partner from a risky one: team, scope, ownership, process and contracts.
Related services
Pairs well with.
SaaS & MVP Development
From idea to paying users, without the rewrite.
- Next.js
- React
- Node.js
Custom CRM Development
A CRM shaped around how your team actually sells.
- Next.js
- PostgreSQL
- Node.js
API Development & Integration
Make the systems you already run talk to each other.
- Node.js
- TypeScript
- GraphQL
Ready to build with ai & llm integration?
Book a free 30-minute scoping call. Tell us the problem and we’ll tell you honestly what it takes to solve it.