DissolveLabs

What we do

We design and build AI products, models, and systems.

• 01AI products, 0 → 1

  We take an idea or a rough prototype and turn it into something people can use: scoped, built, deployed, instrumented. You get a working product and the evaluation harness to know whether it is actually working, not just a demo that lands well in a meeting.

• 02Applied machine learning

  Custom models and data pipelines for problems where off-the-shelf does not fit. We handle the unglamorous parts, including labeling strategy, data quality, drift, and cost per inference, because that is usually what decides whether a model earns its place in production.

• 03LLM and agent systems

  Retrieval, tool use, and agentic workflows built on top of your existing product and data. We focus on what teams underestimate: grounding, failure modes, guardrails, and holding quality steady while models, prompts, and data all shift underneath you.

• 04Evaluation and reliability

  Benchmarks, eval suites, and monitoring so "is this good enough to ship?" gets answered with evidence instead of vibes. Building the measurement layer first is what makes every later decision, from model swaps to prompt changes to cost cuts, cheap and reversible.

• 05Technical advisory

  Architecture reviews, build versus buy calls, and honest assessments of what AI can and cannot do for your roadmap. Useful when you want a second opinion from someone who has shipped this work, not a deck that restates what you already suspect.