AI infrastructure your agency owns, built by the people who built the open source AI stack.
OpenTeams deploys and sustains sovereign AI environments inside your security boundary: cloud, GovCloud, on premises, or disconnected.
Government AI runs on open source, and our team helped build its foundation. We've shaped and maintained foundational tools like NumPy, SciPy, JupyterLab, PyTorch, conda, and Nebari, and are proud to employ some of the most talented AI engineers in the world, proven by our continued contractual engagements with companies such as Meta and Google.
We are the small business prime on CDAO's Joint AI Test and Evaluation Infrastructure Capability (JATIC), operating today in IL5 RDT&E enclaves. Additionally, we work with DARPA, U.S. Army, NIH, NASA, and several research institutions and non-profits to advance and maintain open source AI technologies.
We draw on our industry-leading position in the open source AI ecosystem to deliver specialized solutions in the areas of:
Anything we build for you, you own and control, with no vendor lock.
World class engineers embedded in your program, on your enclave, on your timeline. OpenTeams engineers work inside your environment alongside your team to integrate, harden, and sustain the platform, resolving issues at the source and transferring skills as they go. Cleared personnel available from Secret through TS/SCI.
Field models you can defend to the operational tester and the AO. MOSA-aligned harnesses and reproducible pipelines document performance, robustness, and security, including degraded and disconnected conditions.
Deploy AI solutions inside the authorization boundary you already hold. Nebari platforms on your cloud, GovCloud, hybrid, or on-premises compute inherit the host enclave authorization. No new ATO effort, no vendor lock.
Close vulnerabilities in days, not vendor cycles. Curated, secure Python and AI/ML supply chain, private mirrors for disconnected networks, maintainer-level patching.
Turn legacy data into mission answers, from prototype to production. Connect enterprise systems into a governed foundation; run training, fine-tuning, and deployment on your schedule.
Apply frontier-class LLMs to CUI and above without data leaving your perimeter. Open-weight models behind your firewall with retrieval over your own records. No per-token rent, no external inference.
Automate workflows without losing the audit trail. Guards verify output, Gates route to a human when it matters, and Tracks record every action for oversight and IG review.
Know exactly what stands between your data and a fielded AI capability before you spend a dollar on it. A two-week review of your data, compute, authorization posture, workforce skills, and mission use cases, delivered as a scored gap analysis, target architecture, and authorization inheritance plan you can take straight into a requirements package.
Adoption that survives the pilot and the PCS cycle. We stand up the governance, policy, role definitions, and training that turn a prototype into standard operating procedure: Frames that capture your rules once, Ops your analysts run daily, and a measured adoption plan with named owners, so the capability outlives the people who launched it.
Stand up a full AI platform on your compute in weeks, at zero license cost.
Modular open source stack (core plus 15+ packs) for data science, ML, and model serving. Listed JATIC product.
Rebuild any environment exactly, anywhere, for reproducible results and clean audits.
Reproducibility layer built on pixi and conda; every environment is versioned and exportable at package granularity.
Own your software supply chain and retire registry license fees.
MIT-licensed registry for 40+ package formats, including containers and ML models, with scanning, signing, RBAC, SSO, audit logging, and offline bundles for disconnected networks.
An AI knowledge management environment you own, protecting all of your valuable organizational context and intellectual property. Agency-specific assembly of open source and proprietary components inside your perimeter, maintained by OpenTeams.
Governed Generative and Agentic AI on every analyst's desktop, running on local or Hub-hosted models. Desktop application for combining Frames, running sandboxed Cogs, and scheduling Ops as recurring tasks.
Capture mission context once and reuse it everywhere through a governable and traceable accountability system. Institutional knowledge stays permanently with the agency with no data leaks. Frames carry policy, Cogs do the work, Ops orchestrate outcomes with human checkpoints.
Every AI model you have ever used was trained using elements of our code. We authored and maintain NumPy, SciPy, JupyterLab, conda, Numba, and core parts of PyTorch.
Every data scientist and ML engineer in your organization was taught on the AI toolchain we created. Your workforce is productive on day one, with no retraining and no proprietary lock-in.
For over seven years, the biggest AI companies in the world have had our staff on contract to solve their hardest technical problems: Google, Meta, and the largest banking enterprises.
Proven in DoD AI T&E. Prime on CDAO JATIC with MIT Lincoln Laboratory; AWS GovCloud and on-premises deployments up to IL5 (CUI).
Cleared, senior team. Cleared personnel, Secret through TS/SCI, across program management, solutions architecture, and platform and ML engineering.
1. Assess
✓ You get: target architecture and authorization inheritance plan.
Pilot
✓ You get: AI codebase you own and can grow on
3. Scale and Sustain
MOSA-aligned AI T&E reference implementation with MIT Lincoln Laboratory; AWS GovCloud and on-premises up to IL5.
Reinforced NumPy, SciPy, and JupyterLab for the Science Mission Directorate; Nebari for AI/ML workloads at Langley.
AI/ML workflows in disconnected environments via media-transferable package mirrors.
SBIR Phase II research with MIT CSAIL on secure scientific computing.
RL-SAF and OneSAF simulation integration.
RL-SAF and OneSAF simulation integration.
Led by Travis Oliphant, creator of NumPy and SciPy and co-founder of Anaconda. With sister company Quansight, OpenTeams is the third-largest contributor to PyTorch, behind only Meta and Intel.
Start with a two-week assessment of your data, environments, and mission use cases.
