AI Integration
Harness the power of artificial intelligence to automate decisions, predict trends, and unlock insights from your data.
AI is most useful when it sits inside the tools your team already uses. We connect large language models, machine learning and computer vision to your products, CRMs and internal systems so they answer questions, read documents, flag risks and make routine decisions without extra screens to learn.
We start with one high-value use case, prove it with your real data, then harden it for production with access controls, monitoring and cost limits. You keep ownership of your data and prompts, and you can swap model providers later without a rewrite.
What's included
AI assistants & chatbots
Support, sales and internal knowledge assistants grounded in your documents, with hand-off to a human when needed.
Document & data extraction
Read invoices, forms, KYC documents and emails, then push structured data into your systems.
Predictive analytics
Forecast demand, churn or cash flow from your historical data and surface the results in dashboards.
Computer vision
Inspect products, count stock or verify photos using cameras you already have.
- Machine Learning Models
- Natural Language Processing
- Predictive Analytics
- Computer Vision Solutions
- AI-Powered Chatbots
How we work
- Step 1
Use-case workshop
We map where time and money are lost and pick the use case with the clearest return.
- Step 2
Proof of concept
A working prototype on your real data in a few weeks, with measured accuracy.
- Step 3
Production build
Security, permissions, logging, evaluation tests and cost controls added before launch.
- Step 4
Monitor & improve
We track quality and usage after launch and tune prompts, models and data over time.
Technologies we use
- OpenAI
- Anthropic Claude
- Google Gemini
- LangChain
- Python
- TensorFlow
- PostgreSQL + pgvector
- Next.js
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AI Integration FAQs
Do we need a lot of data to start with AI?
No. Many useful AI features, such as document assistants and chatbots, work from the documents and records you already have. Predictive models need history, and we will tell you upfront if your data is enough.
Is our data safe when using AI models?
We use enterprise API terms that do not train on your data, keep sensitive data in your own database, and add role-based access so people only see what they are allowed to see.
Can you add AI to our existing software?
Yes. Most of our AI work plugs into existing CRMs, ERPs, websites and apps through APIs, so you don't have to replace your current systems.
How long does an AI integration project take?
A focused proof of concept usually takes 3 to 6 weeks. A production rollout with integrations, testing and training typically takes 2 to 4 months depending on scope.
Let's talk about your project
Tell us what you need and we'll reply within 24 hours with next steps.