Generative AI & LLM AppsGenerative AI that answers from your data, not from guesswork.
Copilots, document assistants, chatbots and voice agents grounded in your own knowledge, with evaluation built in from week one. Built for accuracy, cost and privacy, so demos keep working with real users.
- Grounded in your data
- Evaluated before launch
- Private deployment ready
Free 30-minute call with a senior AI specialist. Reply within one business day. Based in Jaipur, working with businesses across India.
- Discovery callFree 30 minutes with a senior specialist
- Scoped first phaseWritten scope, timeline and fixed price
- Build with weekly demosWorking software you can see every week
- Launch and supportGo-live with your team ready, then ongoing support
What is generative AI application development?
Generative AI application development means building products and internal tools on large language models (LLMs), such as assistants that answer from company documents, copilots that draft work or voice agents that handle calls. Stack18 builds these on retrieval-augmented generation (RAG), tests them against evaluation sets and deploys them with access controls and monitoring.
Last reviewed 9 November 2026 by the Stack18 delivery team in Jaipur. Security and AI governance · Pricing · About Stack18
| What it covers | Document assistants (RAG); Copilots for your team; Customer chatbots; Voice agents; Generative AI in your product; Evaluation, safety & LLMOps. |
|---|---|
| Typical first step | RAG Proof of Concept: 3 weeks; fixed price. |
| Next step | Production Build: 8–12 weeks; fixed price. |
| Long-term option | LLM Operations: ongoing; monthly retainer. |
| Measured by | Answer accuracy; Deflection rate; Time to answer; Cost per conversation. Each against an agreed baseline. |
| Governance | Human approval at 5 governance gates before anything reaches production. NDA available on request. |
| Delivery team | Based in Jaipur, India. A senior specialist replies within one business day. |
You need Generative AI & LLM Apps when…
Tap the ones that apply to you.
Generative AI & LLM Apps, end to end.
Each capability is delivered by the same team on the Agentic SDLC, with your approval at every critical step.
Document assistants (RAG)
Ask questions of contracts, manuals and policies, and get cited answers.
- Ingestion of PDFs, sheets and wikis
- Answers with source citations
- Access control by role
Copilots for your team
Assistants embedded in the tools your people already use.
- Drafting and summarising
- Sales, support and finance copilots
- Actions with approval
Customer chatbots
Website and WhatsApp assistants that answer, collect details and hand off cleanly.
- WhatsApp and web chat
- Order, booking and FAQ flows
- Human hand-off with context
Voice agents
Phone assistants for qualification, reminders and routine support.
- Language coverage agreed up front
- Call summaries and CRM updates
- Escalation to a person
Generative AI in your product
Add AI features to a SaaS or consumer product without rebuilding it.
- Content, search and recommendations
- Usage limits and cost controls
- Prompt and model versioning
Evaluation, safety & LLMOps
Know it works, and keep knowing.
- Test sets and automated scoring
- Guardrails and red-teaming
- Cost, latency and quality monitoring
A typical generative AI engagement, week by week.
Senior people lead every phase. Specialised AI agents on the Agentic SDLC handle the repetitive work, and nothing ships without your approval.
Frame the use case
Choose the use case, success measure and the data it will use.
Prepare knowledge
Clean content, set access rules and build the retrieval layer.
Build & evaluate
Build the assistant and test it on real questions and answers.
Pilot
Release to a small group, review real usage and decide how to scale.
Start small. Scale when it works.
Every engagement begins with a short, fixed-price step so you can judge the fit before committing further.
RAG Proof of Concept
Teams testing an assistant that answers from their documents.
- Duration
- 3 weeks
- Pricing
- Fixed price
- One use case and source
- Evaluation set and results
- Go or no-go recommendation
Production Build
Teams ready to launch to staff or customers.
- Duration
- 8–12 weeks
- Pricing
- Fixed price
- Production-grade architecture
- Integration with your systems
- Monitoring and runbook
LLM Operations
Live assistants that need care.
- Duration
- Ongoing
- Pricing
- Monthly retainer
- Quality and cost monitoring
- Content and model updates
- Quarterly review
Free 30-minute use-case and data check
Tell us what you would like an assistant to do and what data it would use. A Stack18 AI specialist tells you what is realistic, what is risky and where to start.
- A view on feasibility
- Data and privacy considerations
- Suggested proof of concept
We agree targets before we start.
Every engagement has a baseline and a target on the measures that matter to you, reported at every read-out.
Where Generative AI & LLM Apps makes the biggest difference.
Manufacturing firm
- Challenge
- Engineers search hundreds of PDFs for specifications.
- What we do
- A private document assistant with cited answers and role-based access.
4 weeks to pilot
Fintech lender
- Challenge
- Customers ask repayment questions on WhatsApp after hours.
- What we do
- A WhatsApp assistant that answers from approved content and escalates to agents.
6 weeks
SaaS company
- Challenge
- Wants an AI feature without exposing customer data.
- What we do
- An in-product assistant with tenant-level data isolation, usage limits and evaluation.
10 weeks
Generative AI & LLM Apps questions.
What is RAG and why does it matter?
Retrieval-augmented generation (RAG) gives a language model access to your own documents at the moment it answers. This keeps answers grounded in your content, lets you show sources and means you can update knowledge without retraining a model.
Will our data be used to train public AI models?
We configure providers so your data is not used to train public models, and we can use private deployments where your data must stay in your own environment.
How do you stop the assistant from making things up?
We ground answers in retrieved sources, require citations, test against an evaluation set and add guardrails that make the assistant say when it does not know. Quality is monitored after launch.
Which models do you use?
We are model-agnostic. We pick the model that best balances accuracy, cost, speed and data requirements for each use case, and design so it can be changed later.
How much does a generative AI project cost?
It depends on scope. We start with a fixed-price proof of concept so you can see accuracy and cost per query before committing to a production build.
Do you provide generative AI and LLM application development in Jaipur and across India?
Yes. Stack18 is headquartered in Jaipur, Rajasthan, and delivers generative AI and LLM application development for businesses across India. You get a free 30-minute call, a fixed-price first step and working software every week, so the engagement works the same whether you are in Jaipur or elsewhere.
Often combined with.
Generative AI often pairs with AI agents and automation to take actions, AI governance and evaluation to control risk, AI product development for AI-first products and data and analytics to prepare the data underneath. See all Stack18 services.
AI Agents & Automation
Governed agents that take real work off your team.
Explore →AI TransformationAI Governance & Evaluation
Policies, testing and approval gates for AI you can defend.
Explore →AI TransformationAI Product Development
AI products that hold up in production, not just in demos.
Explore →Let's scope your Generative AI & LLM Apps project.
Tell us where you are and where you want to be. A senior AI specialist will reply within one business day with next steps.
- Free 30-minute consultation
- Indicative estimate after the call
- NDA available on request