Service 05 · AI Integration
AI integration that does real work, not demos
Pristine integrates AI into existing products and business workflows — customer support chatbots, document processing, recommendation engines and automation. We use leading large language models alongside your own data, with guardrails, evaluation and cost controls, so AI features are accurate, secure and actually used in production.
Overview
What practical AI integration means
AI integration means adding capabilities like understanding text, reading documents, answering questions or making recommendations to software you already run — your website, app, CRM or back office — rather than building a separate AI product nobody opens.
We start from a specific, measurable task: answer 60% of support questions, extract fields from invoices, route tickets, summarise calls. Then we pick the simplest approach that works. Sometimes that's a large language model with retrieval over your documents; sometimes it's a smaller model or plain rules. We tell you which, and why.
Production AI needs more than a prompt. We build evaluation sets to measure accuracy, add guardrails and human review where mistakes are costly, keep sensitive data protected, log every response and monitor cost per request — so you can trust the feature and afford it at scale.
Capabilities
AI Integration services we offer
AI chatbots & assistants
Support and sales assistants trained on your content, with hand-off to humans and multilingual answers.
Document processing
Extract data from invoices, KYC documents, contracts and forms into structured, validated fields.
Search & knowledge bases
Retrieval-augmented search so teams and customers get accurate answers from your own documents.
Recommendation engines
Personalised product, content and next-best-action recommendations based on user behaviour.
Workflow automation
AI steps inside existing processes — classify, route, summarise, draft — with humans approving what matters.
AI features in your product
Summaries, smart search, writing assistance and insights embedded directly into your SaaS or app.
Tools & technology
The stack behind our AI work
- Models
- ClaudeGPTGeminiOpen-source models
- Retrieval
- EmbeddingsVector searchpgvectorHybrid search
- Engineering
- Node.jsPythonTool use & agentsEvaluation suites
- Safety
- GuardrailsPII redactionHuman reviewUsage & cost monitoring
Process
How we deliver ai integration
- 1
Pick one valuable task
We find the workflow where AI saves the most time or money and define how success will be measured.
- 2
Prototype on your data
A working prototype on a sample of your real data shows what accuracy is possible within days.
- 3
Evaluate & harden
We test against an evaluation set, add guardrails and review steps, and tune for cost and speed.
- 4
Ship & monitor
The feature goes live inside your product with logging, feedback loops and ongoing quality checks.
Who it's for
Built for teams like yours
We work with startups, SMEs and enterprises across India and Southeast Asia — in retail, fintech, healthcare and logistics.
Support & operations teams
Cut response times and manual data entry with assistants and document automation.
SaaS & product companies
Add AI features your users will pay for, built into the product they already use.
Fintech, healthcare & logistics
Process documents and data at scale with the accuracy and audit trail regulated work needs.
FAQ
AI Integration: frequently asked questions
What kind of AI can you add to my business?
The most common projects are customer support chatbots, document data extraction, internal knowledge search, recommendations and automating repetitive steps like classifying and routing requests. We start with the task that delivers the clearest return.
Is our data safe when using AI models?
We use enterprise API terms where providers don't train on your data, redact personal information where possible, restrict access by role and can run models in your own cloud account when required.
How accurate is AI document processing?
Accuracy depends on document quality and variety. We measure it on a sample of your real documents before launch and add validation rules and human review for low-confidence results, so errors are caught rather than passed downstream.
Can the chatbot answer in Hindi and other Indian languages?
Yes. Modern language models handle Hindi and many other Indian languages well, and we test answers in the languages your customers actually use.
How much does it cost to run AI in production?
Running costs depend on usage volume and model choice. We estimate cost per request during the prototype, then optimise with caching, smaller models and efficient prompts so the feature stays affordable as usage grows.
Related services
Often paired with
Let's talk about your AI project
Tell us what you need. In a free 30-minute call we'll tell you honestly how we'd approach it — and whether we're the right fit.