cloudfloo.io
02.0SERVICE

AI & MACHINE LEARNINGAI systems your operators can trust.

We introduce AI into real company systems: document flows, support queues, smart factories, approval paths, legacy operations, and ML inference. The model is never the whole product; the controls, evals, latency budget, and rollback path decide whether it survives production.

HOW WE WORK
  1. 01Two-week auditFixed price. Domain map, risks, and a delivery plan.
  2. 02Working sliceOne real workflow shipped end to end.
  3. 03Progressive rolloutTraffic moves in steps; rollback stays ready.
  4. 04HandoffRunbooks, dashboards, and docs your team keeps.
PROOF
IndepAI

AI coach shipped inside a deterministic finance product, bounded by user consent

CloudFloo product portfolio
01

What we build

01

RAG, agents & workflow automation

Retrieval, tool use, approvals, audit logs, and fallback behavior for business-critical flows.

02

Smart factory AI

Machine events, quality gates, maintenance tasks, operator approvals, and legacy system integration.

03

Custom ML & inference

Training, fine-tuning, serving, batching, caching, and model routing by latency and cost.

04

MLOps & evaluation

Drift checks, regression evals, prompt/version control, monitoring, and rollback gates.

02

Stack in production

The tools we run for this work, and what each one is there to do.

PyTorch

Model training and fine-tuning.

Hugging Face

Open-weight models, tokenizers, and eval datasets.

Triton

GPU inference serving with batching.

Ray

Distributed training and batch inference jobs.

Kubeflow

ML pipelines on the Kubernetes you already run.

MLflow

Experiment tracking and model registry.

OpenAI

Hosted models behind our own evals and cost controls.

PostgreSQL

The default system of record.

Kubernetes

Runtime for every platform we operate.

03

What you get

  1. 01AI opportunity map: where agents help, where deterministic software should stay in charge.
  2. 02Working vertical slice connected to one real workflow, dataset, or company system.
  3. 03Eval suite, monitoring, safety checks, and human approval points for risky actions.
  4. 04Cost and latency model: per request, per workflow, and per environment.
NEXT STEP

Start with a two-week audit.

Fixed price. We map the domain, ship a working slice, and hand over documentation your team keeps, whatever you decide next.