02 · Service

AI-Native Product Builds.

AI that ships, not demos.

RAG, agents, multimodal, evals — wired into your product with the prompt engineering and infra to make them reliable in front of real users.

Schedule an intro See client work
What you get

Capabilities, not buzzwords.

LLM applications
OpenAI, Anthropic, open-source. Tool use, structured outputs, streaming UI, retries that don't loop.
RAG + vector search
Chunking strategy, hybrid search, rerankers, citations. I've debugged the bad-recall problem.
Multi-agent orchestration
Planner/executor patterns, human-in-the-loop, traces you can actually read.
Evals + guardrails
Regression suites for non-deterministic output. Cost, latency, and quality tracked the same way you track p99.
Multimodal (vision, voice, video)
Document OCR, image generation pipelines, voice cloning, real-time transcription.
Cost + performance tuning
Caching, model routing, batching. The same answer for a quarter the price.
When to engage

Best fit if you're…

  • +Teams adding AI to an existing product
  • +AI-native startups moving from prototype to scale
  • +Enterprises with one shot to ship a flagship AI feature
How it works

Process.

  1. Week 1Map the user job, pick the right model, define evals before you write prompts.
  2. Weeks 2–5Build, eval, deploy. Iterate on real traffic, not vibes.
  3. Week 6+Cost-tune, harden, hand off — or stay embedded as your AI engineer.
Selected work

Where this showed up.

SafariAIPlusDocs
Next service · 03
SaaS Architecture

Multi-tenant data, auth, billing, infra. Systems designed to hold up at scale — and not require a re-architecture every six months.

Let's build
something
remarkable.

I'm open to a small number of new engagements this quarter. Founders, operators, and product teams — bring me your hardest problem.

Book a Discovery Call eric@campbell.ventures