AI Integration
Embed LLMs, RAG pipelines & intelligent automation into your product.
Custom AI Integration Services We Build
At Bliss Technologies, we design and deploy custom AI solutions that turn raw data into business value. Our engineering team integrates generative AI automation, Large Language Model (LLM) APIs, and intelligent workflows into existing systems. We build secure backend services using Python and Node.js, design intuitive interfaces using React & Next.js, and manage cloud infrastructure via Cloud & DevOps pipelines. Whether you need to augment your team or outsource development, you can hire dedicated AI engineers to build tailored systems, as detailed in our client case studies.
Custom AI Chatbots
GPT-4 or Claude-powered assistants trained on your docs, products, and FAQs. Deployed on your website or app.
Document Intelligence
Upload PDFs, contracts, reports — AI extracts, summarises, and answers questions from them instantly.
Workflow Automation
Connect AI to your tools — auto-reply emails, classify support tickets, generate reports, approve or flag items.
Semantic Search & RAG
Replace keyword search with meaning-aware retrieval. Find the right answer across thousands of documents.
Voice & Speech AI
Speech-to-text, voice commands, and AI-generated voice responses integrated into your product.
AI Analytics & Insights
Natural language queries over your data. Ask questions, get structured answers — no SQL required.
Generative AI Solutions & Real-World Applications
Customer Support Chatbot
AI trained on your product documentation. Handles 80% of support queries automatically, escalates the rest with context.
Contract Review Assistant
Upload any contract — AI highlights risky clauses, missing terms, and required changes within seconds.
Email Triage & Auto-Reply
AI reads incoming emails, classifies intent, drafts replies for approval, and routes urgent items instantly.
Internal Knowledge Search
Ask questions across all your SOPs, wikis, and documents in plain English — instant answers with source links.
Technologies & AI Models We Work With
Complex reasoning, long-context document processing, safe and controllable outputs.
Chat interfaces, multimodal tasks, high-volume API integrations.
Agent pipelines, tool-use, multi-step reasoning chains.
Vector databases for RAG, semantic search, and knowledge bases.
Speech recognition and text-to-speech for voice AI features.
Backend AI services, API wrappers, and data pipelines.
We're model-agnostic. We pick Claude for nuanced reasoning, GPT-4o for speed and multimodal tasks, and open-source models (Llama 3, Mistral) when data privacy requires on-premise deployment.
Our AI App Development Process
We identify where AI adds most value — highest ROI problem first. Not every workflow needs AI.
We review your data sources, documents, and APIs that the AI needs to work with.
Working proof-of-concept in 1–2 weeks. You test it before we build the full integration.
Full API integration with your existing systems, with fallbacks, error handling, and rate limiting.
We instrument the AI output quality, monitor token costs, and iterate on prompt engineering.
Cost of AI Integration Services
Starter AI
- 1 AI use case
- GPT-4 or Claude API
- Basic RAG setup
- Deployed on your domain
- 30-day support
AI Product
- 3–5 AI features
- Custom knowledge base
- Agent pipelines
- Analytics dashboard
- Ongoing prompt tuning
Enterprise AI
- Unlimited features
- Fine-tuned models
- Multi-system integration
- Security & compliance
- Priority retainer
Enterprise RAG in 2026: Building Secure AI Assistants for Private Company Data
Learn how modern enterprises leverage Retrieval-Augmented Generation (RAG) to build secure conversational AI assistants without risking public data leakage.
AI That Works in Production.
Not Just in Demos.
Tell us your use case and we'll build a working proof of concept in 1–2 weeks — before any long-term commitment.