AI automation and AI application development
Puzji adds AI where it measurably saves time or improves quality: assistants that answer from your own documents, agents that handle repetitive steps, and automation that classifies, extracts, summarises, and routes work. Every AI feature is connected to a clear business process with human review and evaluation, so it can be trusted in production.
Where AI helps most
- Support and operations teams answering the same questions from policies, manuals, or past tickets.
- Back-office work that involves reading invoices, forms, contracts, or emails and entering data elsewhere.
- Products that need an in-app assistant, smart search, recommendations, or voice input.
- Teams that want to automate multi-step workflows across tools while keeping a person in control.
What we deliver
AI assistants and copilots
Chat and voice assistants inside your product or internal tools, grounded in your data, with guardrails, usage limits, and clear fallbacks when the model is unsure.
RAG over your documents
Retrieval-augmented generation pipelines that index your documents, retrieve the right passages, and cite sources in answers, so responses stay accurate and current.
AI agents and workflow automation
Agents that call your APIs and tools to complete multi-step tasks, with approval steps, audit logs, and permissions that match your business rules.
Document intelligence
Extraction, classification, and summarisation for PDFs, images, and emails, connected to the systems where the data needs to go.
How we work
- 01
Readiness review
Define the decision or task, the data sources, the acceptable error rate, and where a person must review the output.
- 02
Prototype and evaluate
Build a working prototype on real examples and measure accuracy, latency, and cost before committing to production.
- 03
Productionise
Add authentication, logging, rate limits, monitoring, and model fallbacks, then integrate with your product or workflow.
- 04
Improve
Track quality and usage, collect feedback, and refine prompts, retrieval, or models as needs change.
Technologies we use
- AI model APIs
- Agent workflows
- RAG
- Vector search
- Model Context Protocol
- Python
- FastAPI
- Node.js
- Evaluation and guardrails
See the full Puzji technology stack.
Frequently asked questions
What is RAG and do I need it?
Retrieval-augmented generation lets an AI model answer using your own documents instead of only its training data. If answers must reflect your policies, products, or internal knowledge, RAG is usually the right foundation.
Is our data safe when using AI?
We design AI features so that data access follows your existing permissions, sensitive data is minimised before it reaches a model, and providers are chosen to meet your privacy requirements.
How do you measure whether an AI feature works?
We agree evaluation examples and success metrics at the start, such as accuracy, time saved, or deflected tickets, and test every change against them.
Can AI work in Indian languages and Japanese?
Yes. Modern models handle many languages. We test with real examples in the languages your users speak, including voice input where needed.
Talk to Puzji about AI Automation & Development
Share your goals and current situation. We reply from sales@puzji.com with practical next steps, usually starting with a short discovery call.
Start a conversation