Generative AI Development Company

Production-grade LLM apps, RAG systems, AI agents, and copilots built by senior engineers fluent in OpenAI, Anthropic, AWS Bedrock, and Google Vertex.

  • Shipped 40+ production LLM applications
  • Eval, guardrails, and cost-control baked in
  • Free Gen AI feasibility and ROI session

Get a Free Gen AI Build Plan

Tell us about the Gen AI product you want to build. A senior AI engineer will follow up within one business day.

Generative AI Capabilities

LLM Apps & Chatbots

Production chat experiences with OpenAI, Anthropic, Bedrock, or open-source LLMs — streaming, citations, and conversation memory.

RAG & Knowledge Retrieval

Retrieval-augmented generation on Pinecone, Weaviate, pgvector, or Elastic — chunking, embeddings, and re-ranking that actually work.

AI Agents & Copilots

Tool-using agents, copilots, and workflow assistants that take real actions through your existing APIs and integrations.

Fine-Tuning & Adapters

LoRA, QLoRA, and full fine-tuning for domain-specific models — including evaluation and rollout strategies.

Guardrails & Evaluation

Prompt injection defenses, content filters, eval suites, and red-team testing so your product behaves in production.

Inference Cost Control

Caching, fallback chains, model routing, and per-tenant rate limits to keep inference costs predictable.

Generative AI products that survive production — not just demos.

We design LLM apps, RAG systems, and agents with the eval suites, guardrails, and cost control real products need, so your AI feature behaves the same on Tuesday as it did at the launch demo.

  • LLM apps on OpenAI, Anthropic, Bedrock, Vertex, or open-source models.
  • RAG with Pinecone, Weaviate, pgvector — chunking + re-ranking that works.
  • Eval suites, prompt versioning, content filters, and red-team testing.
  • Model routing, caching, and per-tenant rate limits for cost control.

From AI Demo to Production-Grade Product

Most generative AI projects look great in a demo and fall apart in production. Latency creeps up, costs explode, hallucinations leak into customer experiences, and there's no way to tell whether the model is improving or regressing. We build Gen AI products with the evaluation, observability, and cost control real products require — so your LLM-powered features behave the same on Tuesday as they did at the launch demo.

Maxiom Apps is a generative AI development company that has shipped LLM-powered apps, RAG systems, and agents for fintech, healthcare, SaaS, and enterprise organizations. Our AI engineers are fluent in OpenAI, Anthropic, AWS Bedrock, Google Vertex, and the open-source ecosystem (Llama, Mistral, Mixtral) — and we pair them with product strategists who scope for ROI, not novelty.

  • Production-Grade From v1

Eval suites, prompt versioning, retries, and observability built in from the start — not after the first outage.

  • Model-Agnostic Architecture

Switch between OpenAI, Anthropic, Bedrock, Vertex, or open-source models without rewriting your application.

  • Cost-Aware By Design

Caching, fallback chains, model routing, and per-tenant rate limits to keep inference costs predictable as you scale.

  • Compliance-Aware

Data residency, PII redaction, SOC 2, and HIPAA patterns for regulated Gen AI workloads.

Where Our Work Has Impact

SaaS & B2B Tools

AI copilots, document understanding, and conversational interfaces inside SaaS products.

Healthcare & Life Sciences

Clinical decision support, document summarization, and patient-facing chat with HIPAA-aware engineering.

Financial Services

Compliance-aware copilots, research assistants, and customer service automation for fintech and banking.

Legal & Professional Services

Document analysis, contract review, and knowledge-base assistants for legal and consulting workflows.

Customer Support

Retrieval-augmented support agents that resolve tickets and escalate cleanly to humans.

Internal Productivity

Internal copilots that connect to your data stack, ticketing system, and knowledge base.

How We Build, in Four Phases

  1. Discover

Strip your idea to its core value.

  1. Design

A lean plan that de-risks the build.

  1. Develop

Senior engineers ship in 2-week sprints.

  1. Deploy

Launch, measure, iterate to product-market fit.