# AI Lab, Model Engineering & Evaluation | Kroonen AI > Focused lab engagements to build private AI products, train and adapt models, and stress-test agent systems, with working code, reproducible evaluations, and clean handoff. Canonical: https://www.kroonen.ai/services/ Kroonen AI / Lab engagements # Your AI ambition. A working system. Work directly with the lab to build private AI products, adapt models, and test the limits. From the first technical decision to code your team can own. [Talk about your project ↓](#contact) [See what we’ve built →](https://www.kroonen.ai/projects/) What do you need to do? 1. [01 Build a product Agents, interfaces, and infrastructure ↓](#build) 2. [02 Adapt a model Training, data, and evaluation ↓](#train) 3. [03 Test a system Safety, permissions, and resilience ↓](#stress-test) [Not sure yet? Start a conversation. →](#contact) Jump to [Build](#build) [Train](#train) [Stress-test](#stress-test) [Engagements](#engagements) Capabilities / 01-03 ## Three ways we do deep work. Choose a starting point below. Each engagement has a defined outcome, with the code, evaluations, and documentation to support it. 01 Build ### Take your AI product into production. We design agent workflows, private interfaces, communications systems, and the infrastructure that keeps them useful in production. [Discuss your product →](#contact) Useful when You know the outcome, but the system crosses product, model, data, and infrastructure boundaries. #### Scope can include - Agent runtimes, tools, permissions, and orchestration - Self-hosted or hybrid inference, RAG, and private interfaces - Web, mobile, voice/SMS, and operational workflows - MCP servers, provider adapters, and existing-system integrations #### You receive - ✓ Architecture and decision record - ✓ Working implementation and deployment - ✓ Tests, documentation, and operational runbook - ✓ Clean handoff to your team Lab proof [Libre Claw · Libre Phone · Libre WebUI →](https://www.kroonen.ai/projects/) 02 Train ### Give your model the behavior you need. We handle data, fine-tuning, evaluation, and from-scratch training when prompting an API no longer solves the real problem. [Discuss your model →](#contact) Useful when The product needs behavior, cost, latency, language coverage, or ownership that an off-the-shelf endpoint cannot provide. #### Scope can include - Feasibility, architecture, and model selection - Dataset curation, deduplication, and synthetic data - Fine-tuning and distributed model training - Capability, behavioral, and domain evaluation #### You receive - ✓ Reproducible data and training recipe - ✓ Checkpoints and inference package - ✓ Evaluation report and known limitations - ✓ Deployment and iteration plan Lab proof [Genesis 1B · 80,000 steps · 2× RTX 4090 →](https://www.kroonen.ai/blog/genesis-training-progress/) 03 Stress-test ### Understand the risks before you deploy. We test models and agent systems where prompts, tools, permissions, and sensitive data meet, then turn the findings into concrete engineering work. [Discuss an evaluation →](#contact) Useful when Your model or agent can reach tools, private context, external systems, or users who will behave unpredictably. #### Scope can include - Prompt injection, jailbreaks, and system-prompt leakage - Tool misuse, permission abuse, and data-exfiltration paths - Behavioral drift and domain-specific evaluation - Agent boundaries, provider fallbacks, and failure recovery #### You receive - ✓ Threat model and prioritized test plan - ✓ Reproducible evaluation suite - ✓ Risk-ranked findings and evidence - ✓ Remediation plan and retest Typical artifact Threat model · Eval suite · Remediation record Lab proof / Built here ## We build before we advise. These are lab products and research programs, not borrowed case studies or anonymous client claims. [Explore the complete portfolio →](https://www.kroonen.ai/projects/) [01 Train Genesis 1B 1B parameters · 80,000 steps · 2× RTX 4090 →](https://www.kroonen.ai/blog/genesis-training-progress/) [02 Build Libre Claw Permissioned tools · local memory · multi-provider ↗](https://libreclaw.sh) [03 Build Libre Phone Voice · SMS/MMS · IVR · Cloudflare Workers ↗](https://libreph.one) Ways to work / Clear start, clean handoff ## Choose the smallest useful engagement. The commercial shape follows the work: fixed scope for a diagnostic, milestones for a build, or reserved capacity for ongoing R&D. 01 Fixed scope ### Technical diagnostic One hard product, architecture, model, or risk question. We reduce the uncertainty before anyone commits to a larger build. Output Decision memo, system or risk map, and a scoped next move. [Discuss this engagement →](#contact) 02 Milestone-based ### Focused build A working system or clearly defined model/evaluation milestone, built with visible technical checkpoints. Output Working artifact, tests, documentation, deployment, and handoff. [Discuss this engagement →](#contact) 03 Reserved capacity ### Embedded lab Ongoing iteration for programs where research, product, and operations need to stay tightly coupled. Output Continuous builds and evaluations with a direct working cadence. [Discuss this engagement →](#contact) 01 ### Frame Name the constraint and the decision it blocks. 02 ### Prove Retire the hardest technical risk first. 03 ### Build Turn the evidence into a working system. 04 ### Transfer Leave code, tests, docs, and ownership behind. Direct technical access The people scoping the system are the people building it. Artifacts over theater Working code, evaluations, and decisions, not recurring slide decks. Handoff without lock-in Source, documentation, and operational knowledge move with your team. Let’s work together ## Tell us what you have in mind. Share the idea, the challenge, or the system you want to improve. You don’t need a finished brief to start a conversation. 01The decision or outcome you need 02The hardest technical constraint 03Any timeline or operational boundary Prefer a direct note? [hello@kroonen.ai](mailto:hello@kroonen.ai)·[+1 (916) 999-5979](tel:+19169995979)