Generative AI Development Company

Generative AI Development That Turns Your Data Into Answers, Not Just Text

Anviam builds custom LLM applications, RAG-powered knowledge tools and AI copilots that generate accurate, on-brand output grounded in your own content, plus straightforward ChatGPT and Claude integration for products that just need the model plugged in correctly.

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Generative AI, Explained

More Than a ChatGPT Wrapper

Generative AI covers a wide range of work, and most of it isn't as simple as calling an API. ChatGPT integration means wiring the model into your product's existing UI and data flows correctly, with proper error handling and cost controls. RAG development services ground the model's answers in your own documents and databases instead of its general training data, so responses stay accurate and current. Custom LLM applications go further still, combining retrieval, business logic and your own UI into a purpose-built tool rather than a chat window bolted onto the side of your product.

An AI copilot sits on top of all of this: a focused assistant embedded in your product or intranet that answers questions, drafts content or summarizes records using your company's own data. As a generative ai consulting services partner, we help you work out which of these you actually need before any code gets written. And if what you're after is a system that takes action rather than generates content, see our AI Agent Development services instead.

What We Build

Generative AI Development Services

Every engagement starts with your data and use case, not a demo. We scope it as large language model development work built to run in production, not a proof of concept.

Custom LLM Application Development

Purpose-built applications that combine an LLM with your business logic, data and UI, not a generic chat interface but a tool designed around one job.

RAG Development Services

Retrieval-augmented generation pipelines that ground model output in your documents, tickets or product data, cutting down on made-up answers.

ChatGPT, Claude & Gemini Integration

Clean, production-grade integration of OpenAI, Anthropic or Google models into your existing product, with proper rate limiting, logging and fallback handling.

AI Copilot Development

Embedded assistants that give your team or your customers a single, trustworthy interface into company data, documentation or product features.

Prompt Engineering & Fine-Tuning

Structured prompt design, evaluation and, where retrieval alone isn't enough, fine-tuning to get consistent tone, format and domain accuracy.

Generative AI Consulting & Strategy

An honest assessment of where generative AI fits your business, what it will cost to build well, and where it isn't the right tool for the job.

Use Cases

Generative AI by Function

Customer Support Copilots

Assistants that draft replies from past tickets and documentation, so agents review and send instead of typing from scratch.

Content & Marketing Generation

Tools that generate first-draft copy, product descriptions and campaign variants grounded in your brand guidelines and past content.

Internal Knowledge Assistants

RAG-powered assistants that answer employee questions from internal wikis, policies and past decisions instead of a search bar full of links.

Healthcare Documentation

Generative tools that draft clinical notes and summaries from visit transcripts, reviewed and signed off by clinicians, inside HIPAA-compliant workflows.

Developer Copilots

Internal coding assistants trained on your own codebase and documentation, so suggestions match your actual patterns, not generic examples.

Sales Enablement

Tools that generate call summaries, follow-up emails and account briefs pulled straight from CRM notes and past correspondence.

Our Process

From Use Case to Production LLM Application

Discover the Use Case & Data

We map what content or data the model needs access to and where the risk of a wrong answer is highest.

Design the LLM Architecture

We decide between retrieval, fine-tuning or a combination, and pick the model that fits your cost and latency needs.

Build & Evaluate

We build against real prompts and measure answer quality and grounding, not just a polished demo.

Integrate & Pilot

The application runs alongside your team on live content before it's rolled out to everyone.

Deploy & Monitor

Production deployment with usage logging, cost tracking and ongoing prompt tuning.

FAQ

Common Questions About Generative AI Development

Generative AI focuses on producing content like text, code, summaries and images from a prompt. An AI agent takes that a step further: it plans steps, calls tools and APIs, and completes multi-step tasks with minimal human input. Many of our generative AI projects sit underneath an agent, but the two are scoped and built differently.

A single-purpose LLM application, such as a support copilot or an internal knowledge assistant, typically takes 6 to 10 weeks from discovery to production. Projects involving custom fine-tuning or multiple integrated data sources usually run 10 to 16 weeks.

Yes. Most of our chatgpt integration services connect directly to your existing application through the OpenAI API, so the model works against your live data and UI rather than a separate bolt-on tool. We also support Anthropic Claude and Google Gemini if you'd rather not depend on a single vendor.

For most business use cases, yes. RAG (retrieval-augmented generation) keeps your data separate from the model and lets you update answers by updating documents, not retraining anything. Fine-tuning is worth the extra cost and time mainly when you need the model to consistently follow a very specific tone, format or domain-specific reasoning pattern that retrieval alone can't teach it.

Yes. Our generative ai consulting services include a standalone assessment, reviewing your data, use cases and risk constraints, and a recommendation on whether generative AI is worth building for your situation, with no obligation to continue into development.

Yes. Beyond fixed-scope projects, you can hire llm developers from Anviam as a dedicated, embedded extension of your team on a monthly staff-augmentation model.