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Core AI / Arvo Labs

Custom AI & LLM Integration

RAG pipelines, agents, and custom AI built on your data.

Engagement outline
  1. 01Understand
  2. 02Make a plan
  3. 03Review together
Core AI

The opportunity

Generic chatbots don't hold up in production. We engineer enterprise RAG systems, model routing logic, and specialized agent workflows trained on your proprietary data. Every build includes evaluation benchmarks (evals), rate limiting, and prompt guardrails to guarantee sub-second latency and near-zero hallucination.

The work, made tangible

What you receive.

01

Vector Search & Retrieval Pipeline

Chunking, embedding, and hybrid search optimization over your knowledge base.

02

Agentic Workflow Orchestration

Tool-using AI agents that read APIs, execute database queries, and perform structured tasks.

03

Human-in-the-Loop Exception Queues

Routing low-confidence AI predictions to human reviewers before final output.

Tools & technology

  • Python
  • TypeScript
  • OpenAI API
  • Anthropic SDK
  • LangGraph
  • FastAPI
  • PostgreSQL/pgvector
  • Redis

Before we begin

A few useful answers.

How do you prevent AI hallucinations in production?

We enforce strict retrieval-augmented generation (RAG) with ground-truth citations, confidence scoring, and fallback routing to human reviewers when confidence is low.

Is our proprietary data kept private?

Yes. All engagements operate under NDA. We use zero-retention enterprise API endpoints or self-hosted open-source models.

Can we switch AI models later without a rebuild?

Yes. We put a provider abstraction between your application and the model, so moving between vendors is a configuration change plus a round of evals rather than a rewrite. Given how fast pricing and capability shift, assuming today's model is permanent is a mistake.

Let’s make it happen

Let’s talk about
your next step.

RAG pipelines, agents, and custom AI built on your data.

Discuss your project