imaged Lab

Your data. Your model. Our engineering.

Lab takes on the hard parts: fine-tuning, integration, and the engineering in between. You bring the problem and the data. We deliver a working model, in your codebase, owned by your team.

What we do

Three kinds of engagement. Clear edges.

Every project has a defined outcome, a fixed price, and a delivery date agreed up front. No hourly, no open-ended.

01

Fine-tuned vision models

Detect what you actually ship (defects on your production line, signs in your documents, patterns on your scans), not what happens to be in open datasets.

  • Object detection, segmentation, classification, or embeddings
  • Trained on your labeled data, under NDA
  • Delivered as an ONNX model + one-line integration into the SDK
Typical · 4 to 6 weeks
02

Fine-tuned LLMs

Your domain, in a model that fits under your GPU budget. Fine-tuned on your corpus, packaged to run locally on Hugind. No API calls leave your network.

  • Fine-tune on open-weight bases (Llama, Gemma, Qwen, Mistral)
  • Quantized to GGUF for laptop and single-GPU deployment
  • Shipped with a Hugind config and eval report against your tasks
Typical · 4 to 6 weeks
03

Integration & consulting

Get the imaged SDK or Hugind running end-to-end in your app, on your infrastructure, in weeks, not quarters. Plus an architecture review if you want a second opinion before you start.

  • Native integration (iOS, Android, macOS, Linux, Windows)
  • On-prem deployment, air-gapped environments welcome
  • Architecture review, code review, or embedded engineering
Scoped per project
How we work

Four steps. No discovery phase.

The first call decides whether we’re the right fit. If we are, the proposal goes out within a week.

  1. Step 01

    Call

    30 minutes. You describe the problem, the data, the deadline, and the constraints. We say whether we can help.

  2. Step 02

    Proposal

    Within a week: fixed scope, fixed price, fixed delivery date. One page. You approve in writing, we start.

  3. Step 03

    Build

    Weekly check-ins with working code or a working checkpoint. No slide decks. If something is off track, you hear it the same week.

  4. Step 04

    Hand-off

    Code in your repo, model on your hardware, documentation your team can actually read. We stay on standby for two weeks after.

Honest fit

We’re not for everyone. Here’s who we are for.

Good fit when
  • You already have labeled data, or a clear path to collect and label it within the engagement.
  • You know the output you need (detections, classifications, structured extractions, summaries) and you can show us a good example.
  • You want the result in your codebase, not behind someone else’s API. Ownership, offline, or both.
  • You have a deadline (regulatory, commercial, or product-launch) and a fixed budget to match.
Not a fit when
  • You’re still validating whether AI can help at all. Hire a short-term consultant first; come back when the question is how, not whether.
  • You need a GenAI chatbot bolted onto your public site. Plenty of agencies do that well; we don’t.
  • You want a free pilot. The imaged SDK trial and Hugind (MIT) are the free path; Lab engagements are paid from day one.
Ready?

Tell us what you’re trying to ship. We’ll tell you whether we can help.