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02 / Custom LLM & Generative AI Apps

Custom LLM and generative AI app development, tested on your data.

AI assistants, chat over your documents and copilots inside your tools, built on large language models and tested against real examples before launch.

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6 to 10 weeks · fixed price after a one-week discovery

Fig. 05 / Crodo, answers about what is on your screenOUR PRODUCT
INVoice and screen capture
LLMLanguage model with screen context and tools
OUTAnswer, note, or action in Gmail, Calendar, Slack

What we build

What you get: specific deliverables, not a list of capabilities.

01Chat over your documents (RAG)Ask questions across contracts, manuals, tickets or policies and get answers with the source shown. Works with your permissions, so people only see what they are allowed to.
02AI assistants with memoryCustomer-facing or internal assistants that remember the conversation and the customer, and hand over to a person cleanly when needed.
03Copilots inside your toolsSummaries, drafts and suggestions inside the CRM, helpdesk or admin panel your team already uses, instead of another tab to open.
04Document and content generationProposals, reports, product descriptions and emails written from your data in your tone of voice, and reviewed by a person before they go out.
05Testing and quality checksA set of real questions with known correct answers, checked automatically every time the app changes, so quality never drops without you knowing.

What we build with large language models

Generative AI is easy to demo and hard to ship. A demo answers three questions well. A product has to answer ten thousand, show where each answer came from, refuse what it should not answer, and cost less to run than the person it helps.

We have shipped this for our own products. Crodo answers questions about whatever is on your screen and takes actions in your apps. Building it taught us more about search, speed and cost than any client brief could, and that experience goes into your project.

How an LLM app is built

Fig. 05 / Crodo, answers about what is on your screenOUR PRODUCT
INVoice and screen capture
LLMLanguage model with screen context and tools
OUTAnswer, note, or action in Gmail, Calendar, Slack

Our LLM app development process

  1. Discovery, week 1. Which questions, which documents, which users. We collect a sample and write the first fifty test questions with you.
  2. Prototype, weeks 2 to 3. Search and answers on your real documents, scored against the test questions. We compare two or three models on quality, speed and cost.
  3. Build, weeks 4 to 10. Permissions, the interface inside your tools, cost controls, monitoring and weekly demos.
  4. Run. Quality dashboards, a monthly review of wrong answers, and improvements on a retainer or a full handover.
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Frequently asked questions

Common questions about Custom LLM & Generative AI Apps.

What is an LLM app?

An LLM app is software built on a large language model such as GPT, Claude or Gemini. The model reads and writes text; the app around it adds your data, your rules, a user interface and checks on quality. Chat over documents, AI assistants and writing tools are all LLM apps.

What is RAG and why does it matter?

RAG (retrieval-augmented generation) means the app first finds the relevant parts of your own documents and then asks the model to answer using only those. It is how an AI assistant answers from your policies or manuals instead of guessing, and it lets every answer show its source.

How do you deal with wrong or made-up answers?

Answers show their sources, low-confidence questions go to a person, and we measure the rate of wrong answers on a test set before and after every change. You see that number and you decide what is acceptable.

Which AI models do you use?

Whichever fits the job: OpenAI, Anthropic and Google models through their APIs, or open models such as Llama, Mistral and Qwen hosted privately when your data must stay in a particular place or costs need to be lower. We compare candidates on your data before choosing.

Will our data be used to train someone else's model?

No. We use API terms that exclude training, or host the model ourselves. Your documents stay in your cloud or ours under NDA, personal data is removed before it reaches a third-party model, and we never train on client data.

What does an LLM app cost to run each month?

We estimate usage and hosting costs from the prototype's real traffic and design to keep them down, with caching, smaller models for simple steps and batching. The monthly cost is part of the decision to go live, not a surprise afterwards.

Related AI services

01AI Agents & Workflow AutomationAI agents that handle support tickets, documents, research and back-office work for you, and ask a person when they are unsure.05AI Product & MVP DevelopmentFrom idea to a launched AI product in 8 to 12 weeks, the same way we launched our own products Decornoa, Crodo and TurboType.

Next step

Tell us what you want to build. We will tell you what it costs and how long it takes.

A free 30-minute call with an engineer, not a salesperson. You leave with a clear plan, a price range and an honest opinion on whether AI is the right tool for the job.

Book a free AI strategy call WhatsApp us+91 93998 98342Or write to us contact@appwizards.in