Key Takeaways
- Start with AI features that save users time: search, summaries and document extraction.
- Use retrieval (RAG) so AI answers come from your own data.
- Monitor accuracy, cost and privacy from day one.
AI APIs make it practical for SMEs and startups to add intelligent features without building models from scratch.
9 AI features to consider
- Semantic search that understands meaning, not just keywords
- In-app AI assistant answering questions from your help docs and data
- Document extraction from invoices, IDs, forms
- Summaries of long records, tickets or reports
- Recommendations for products, content or next actions
- Forecasting of demand, churn or revenue
- Content generation for descriptions, emails and replies (with review)
- Anomaly detection for fraud or errors
- AI agents that complete multi-step tasks with approval
Implementation approach
| Need | Approach |
|---|---|
| Answers from your data | Retrieval-augmented generation (RAG) |
| Structured extraction | LLM or OCR with validation rules |
| Predictions | ML models trained on history |
| Actions | Agents with permissions and human approval |
Responsible AI
- Protect personal data; follow DPDP principles
- Show sources for AI answers
- Keep humans in the loop for consequential actions
- Track cost per request
See AI-powered dashboards and AI in ERP.
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Frequently Asked Questions
How can I add AI to my web app?
Through AI APIs for language, vision and prediction, integrated via your backend with proper data handling and user interfaces.
What is RAG?
Retrieval-augmented generation lets an AI model answer questions using relevant documents or data retrieved from your own systems.
Is AI integration expensive?
Costs depend on usage; many features can be added affordably with pay-per-use APIs.
Is it safe to send data to AI APIs?
With trusted providers, data-processing agreements, minimisation and masking of sensitive data, risks can be managed.
