Generative AI, ready for production
Chatbots, copilots and content tools built on LLMs and grounded in your own data: safe, accurate and measurable.
Can a customer return a custom-made order?
Our venture · Kalindi
Shoppers just say what they want. Sakhi finds it.
Kalindi sells ethnic women's wear online. Sakhi, its AI style assistant, understands requests in everyday Hinglish, so shoppers no longer dig through filters to find the right piece.
Category
- Sarees
- Kurta sets
- Kurtis
- Co-ords
Colour
- Red
- Blue
- Pastel
- Green
Price
- Under ₹1,000
- ₹1,000–2,000
- ₹2,000–5,000
All products · sort by: newest
- Understands Hinglish
- Gift finder in 3 questions
- Occasion, colour and budget in one sentence
Use cases
Where Generative AI & LLM Integration creates practical value.
Focused applications shaped around the people, workflows and outcomes behind the product.
Deliver instant, human-like answers grounded in your product docs, handle order inquiries, and intelligently triage edge-case tickets to human agents.
Business outcomes
What Generative AI & LLM Integration should improve.
The engagement is shaped around useful, maintainable outcomes—not output for its own sake.
Hallucination-Free Responses
100% Private Cloud Deployment
Sub-Second Latency Caching
Enterprise Data Governance
Instant Source Citations
70% Reduction in Operational Costs.
Typical deliverables
- Model / LLM selection
- Use-case discovery
- Technical architecture
- Evaluation & guardrails
- Secure integration
- Secure APIs
- Backend & APIs
- Test cases & automation
- CI/CD & hosting setup
- Monitoring & iteration
- Documentation & handover
- Post-launch support
Capabilities
Generative AI & LLM Integration, end to end.
Each capability can stand alone or connect into a wider product engagement.
Enterprise RAG & Hybrid Vector Search
Ground LLM outputs in your private databases, documents, and live APIs using multi-vector indexing, re-ranking, and zero-hallucination pipelines.
Context-Aware In-App Copilots
Embed conversational copilots directly into your web, mobile, and desktop applications to guide users, automate actions, and draft workflows.
Multi-Modal Content & Data Generation
Automate high-throughput structured data extraction, document summarization, reporting, and on-brand creative asset generation at enterprise scale.
LLM Fine-Tuning & Model Alignment
Domain-specific fine-tuning (LoRA, QLoRA) and RLHF/DPO alignment to adapt open-source and proprietary models to your company's proprietary terminology.
AI Guardrails, Red-Teaming & Governance
Deterministic PII masking, automated prompt injection defenses, hallucination checks, and compliance filters to ensure bulletproof enterprise security.
Delivery approach
How we deliver Generative AI & LLM Integration.
Clear stages make decisions visible and keep design, engineering and quality aligned.
- 01
Model Selection & Feasibility Benchmark
We evaluate your specific use case, benchmark frontier vs. open-source models for cost and latency, and establish domain-specific evaluation metrics.
- 02
Data Ingestion & Hybrid RAG Architecture
We design chunking strategies, set up vector embeddings, configure hybrid search indexes, and wire direct connectors into your enterprise data sources.
- 03
Guardrails, Evals & Security Sandboxing
We implement strict output validation, adversarial prompt injection defenses, real-time PII anonymization, and automated regression benchmark suites.
- 04
Cloud Deployment & Telemetry Setup
We deploy the solution into your private AWS/GCP cloud with semantic caching, token usage tracking, and real-time observability dashboards.
Technology
Fit for the product.
- OpenAI
- LangChain
- Python
- PostgreSQL
- Supabase
- AWS
- TypeScript
- Next.js
- Node.js
FAQ
Questions, answered.
Useful context before starting a Generative AI & LLM Integration engagement.
Where ideas meet technology.
Ready to discuss Generative AI & LLM Integration?
Share your goals, constraints and current stage. We will help define the most practical next step.
Your next step
- 01Share your goals
- 02Clarify the right scope
- 03Plan the next practical step