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Data agents
Agents that connect to your databases, tools, and SaaS apps, reason over what they find, and take action with evals and human review where it counts.
e.g. nightly invoice reconciliation across three systems
ZeroTwo Labs designs, builds, and operates the AI, and the systems, apps, and workflows around it. End-to-end, for teams that want working products, not research papers. Tell us what you're stuck on; we ship it.
Four shapes of AI problem we take end-to-end: strategy, build, deploy, operate. If your problem looks AI-shaped, we should talk.
Agents that connect to your databases, tools, and SaaS apps, reason over what they find, and take action with evals and human review where it counts.
We process surveys, transcripts, tickets, and calls at scale, then hand stakeholders the briefs and dashboards they'll actually read.
We deploy and run open-weights models on your own infrastructure, with routing, autoscaling, and monitoring included, at a fraction of API cost.
Most problems don't fit a neat category. If it can be solved, or made meaningfully better, with AI, that's our favorite kind of project.
Four years of engagement notes, distilled into a short list of things we do well. We don't write reports; we ship and operate.
Multi-region GPU fleets, request routing, observability, autoscaling. We run the boring layer so your team ships the interesting one.
Production agent loops with evals, guardrails, and human-in-the-loop. Built for tasks your support and ops teams are already doing.
Fine-tunes, distillations, and from-scratch training for teams whose problem doesn't fit a general-purpose model.
We stay on after launch: versioning, regressions, capacity planning, cost. Weekly reports your CFO will actually read.
Short, technical write-ups of what we're shipping. No thought leadership: just the parts that took us longer than they should have.
How we wire retrieval, evals, and human review so agents stay tethered to source data, and how we know when they're drifting.
Read entryA walkthrough of the routing, batching, and quantization tricks we use to run open-weights models on client GPU fleets without blowing budget.
Read entryHow a small pipeline of classifiers, clustering, and LLM summarization turned a year-end HR survey into a 6-page brief leadership actually read.
Read entryWe're researchers, engineers, and operators who would rather ship one thing that works than ten that don't. If our mission resonates, we'd love to talk: whether for client work, a research role, or a coffee.