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// r7-001 · system online · est. 2024

Applied AI, engineered for production.

r7labs is an applied AI lab. We research, develop, and deploy intelligent systems for teams across healthcare, finance, security, and beyond — AI that ships into real workflows, not slideware.

Start a project What we do
12+
AI systems in production
8
verticals served
0
demo-ware shipped
LLM Agents● Retrieval (RAG)● Fine-tuning● Evaluations● Computer Vision● Speech & Audio● Forecasting● Document AI● Multimodal● MLOps● LLM Agents● Retrieval (RAG)● Fine-tuning● Evaluations● Computer Vision● Speech & Audio● Forecasting● Document AI● Multimodal● MLOps●
[ 01 ] services

Three ways we partner with your team.

Most engagements blend all three. We mix and match — strategy when you need direction, implementation when you need to ship, training when you need your team to own it long-term.

01 — consulting

AI Consulting

Strategy from people who actually ship.

Most AI advice comes from firms that have never put a model into production. We help leaders pick the right problems, the right approaches, and avoid the expensive detours — grounded in what actually works at the seams.

  • Strategy & roadmap
  • Use-case discovery & prioritization
  • Build vs. buy analysis
  • Model & vendor selection
  • Risk, governance & compliance review
  • ROI modeling & business case
For leaders making first or next-stage AI bets.
02 — implementation

AI Implementation

From prototype to production.

We build the systems. Agents, retrieval pipelines, fine-tuned models, and multimodal stacks — engineered for the parts of production that demos never show: latency, cost, reliability, and the failure modes you only learn about at 3am.

  • LLM agents & tool-use systems
  • Retrieval-augmented generation (RAG)
  • Fine-tuning & custom models
  • Multimodal pipelines — vision, speech, document AI
  • Evals, guardrails & observability
  • Integration into your existing stack
For teams who need a system, not another demo.
03 — training

AI Training

Upskill your team on the real stack.

Most AI training is slideware. We coach engineering, product, and leadership teams on the same techniques we use in production — hands-on labs and real code, with a curriculum tailored to your stack and your goals.

  • Hands-on workshops (1–3 days)
  • Embedded coaching & pair programming
  • Executive briefings for leadership
  • Custom curriculum for your stack
  • Eval-driven exercises on real data
  • Ongoing office hours & reviews
For organizations that want to own this long-term.
[ 02 ] principles

How we think about applied AI.

  1. P.01

    Eval-driven

    We measure what works. No vibes, no demo theater. Every system ships with a test set we can defend in a room full of skeptics.

  2. P.02

    Production-first

    If it doesn't survive a Tuesday at 3pm, it doesn't ship. We design for latency, cost, and reliability from day one — not as a phase-two retrofit.

  3. P.03

    Embedded

    We work as part of your team, not a vendor at arm's length. Same Slack, same standups, same on-call. Knowledge stays with you when we leave.

  4. P.04

    Vendor-agnostic

    We pick the model that fits your problem, not the one with the best margin or the loudest CEO. Frontier, open, or fine-tuned — whatever earns its keep.

[ 03 ] process

From eval set to production. Then we keep training.

  1. Phase 01

    Discover

    One week. We map the workflow, find the leverage point, and scope the smallest experiment that can prove the thesis.

  2. Phase 02

    Prototype

    Two weeks. Pick the model, build the eval set, ship a working slice end-to-end. Bring data, not slides.

  3. Phase 03

    Productionize

    Latency, cost, reliability, guardrails. The boring engineering that turns a notebook demo into a dependable system.

  4. Phase 04

    Operate

    Continuous evals, drift monitoring, retraining loops. Most clients keep us as their AI team for the long haul.

[ 04 ] training programs

We also teach what we build.

Most AI training is slideware. We coach engineering, product, and leadership teams on the same techniques we use in production — agents, retrieval, evals, fine-tuning — with hands-on labs and real code.

01

Workshops

One- to three-day intensives for engineering and product teams. Pick the modules: agent design, retrieval systems, evals, prompt engineering, fine-tuning. Hands-on from hour one.

  • Agents
  • RAG
  • Evals
  • Fine-tuning
02

Embedded coaching

A senior practitioner pairs with your team week over week. Code reviews, design sessions, and pair programming on the hard parts of shipping AI into production.

  • Pairing
  • Code review
  • Mentorship
  • Design
03

Executive briefings

Half-day sessions for leadership teams. Where AI actually creates leverage, where it doesn't, what to invest in this quarter, and what to skip entirely.

  • Strategy
  • ROI
  • Roadmaps
  • Risk
[ 05 ] let's build

Have an AI initiative
that needs to ship?

We take on a small number of engagements each quarter — across healthcare, finance, security, and beyond. If your initiative sounds like a fit, drop us a line.

support@r7labs.io