What we do differently

Fix first

Audit before building

Most AI implementations underperform. We benchmark accuracy, latency, and cost-per-inference before writing any new code. Fix what exists before adding complexity.

Tiny models

Compress for the edge

Quantization (INT4/INT8), pruning, and distillation. We deploy models where they need to run—on-device, at the edge, without cloud dependency.

Edge-native

Cloudflare-first architecture

Inference on Cloudflare Workers. State in D1 and R2. Vector search with SQLite and sql-vec. No centralized infrastructure to manage.

Measurable

Before/after metrics

Every engagement ships with comparison dashboards. Latency percentiles, accuracy scores, cost-per-inference, and reliability metrics—documented and verifiable.

Productized

Fixed-scope services

Clear deliverables and pricing. No open-ended consulting engagements. You know what you get and what it costs before we start.

Low risk

Test-run model

Start with 10–20 hours a week at $250/hr. See results in the first month. Scale up, move to a retainer, or walk away.

Tech stack

Models & inference

  • Gemini Flash
  • GLM 4.7 Flash on Cerebras
  • Claude SDK
  • ONNX Runtime
  • TensorFlow Lite

Infrastructure

  • Cloudflare Workers
  • Cloudflare Pages
  • Cloudflare D1 / R2
  • SQLite + sql-vec
  • Postgres

Frameworks & observability

  • Pydantic AI
  • FastAPI
  • Pydantic Logfire
  • TinyML tooling
  • Model quantization (INT4/INT8)

Market context

$27B → $143B
Edge AI market by 2034 — 21% CAGR
Precedence Research
81%
of companies fear missing the edge AI window
AlphaSense
22.9% CAGR
Edge AI consulting — fastest-growing segment
GlobeNewsWire

Team

VectorLab is a focused consultancy built by engineers who ship edge AI to production. We work with a small number of clients at a time to maintain quality and depth.