Measurable AI research and infrastructure advantage
AI research collaborations
Institutions we work with on AI science and applied evaluation. Together we co-develop methodology, benchmarks, and paths from AI research into production AI infrastructure. Climate+Tech is our related open knowledge and partner ecosystem—see climateandtech.com for background.
Three pillars of AI independence
TEAM TRAINING
Your team needs to understand AI - not just use it. We run intensive training programs that turn your developers into AI-native builders. Curriculum developed with university partners from AI research, battle-tested in production environments.
BENCHMARKS & EVALUATION
If you can't measure it, you can't improve it. We install rigorous evaluation frameworks that tell you exactly how your AI systems perform - and where the opportunities are. Clear metrics you can defend internally.
ON-PREMISE OPEN SOURCE
Run state-of-the-art AI infrastructure on your own hardware. We implement complete on-premise stacks using open-source models: Llama, Mistral, and beyond. Your data never leaves your servers. Your models never get deprecated by a vendor.
What we deliver
AI Readiness Assessment
Where does AI make sense for your business? Where is it hype? We cut through the noise with a clear-eyed analysis of opportunities and realistic ROI expectations.
Custom Benchmark Suite
Generic benchmarks tell you nothing about your use case. We build evaluation frameworks specific to your domain, your data, your success metrics.
On-Premise Infrastructure Rollout
Complete AI infrastructure on your hardware: model serving, vector databases, fine-tuning pipelines, monitoring. Open source, so you're never locked in.
Team Upskilling Program
From prompt engineering to model fine-tuning to MLOps. We train your team to own and evolve your AI capabilities long after we're gone.
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The hidden cost of AI APIs
Every query to external AI providers: costs money, sends your data to their servers, can change behavior without notice. For competitive advantage, you need AI infrastructure you control. Open-source models are now good enough - the question is whether you have the expertise to deploy them.
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Science beats intuition
Is your RAG system actually improving answers? Is your fine-tuned model better than the base? Most teams are guessing. Our benchmark frameworks from AI research give you real numbers: precision, recall, latency, cost per query. Make decisions based on evidence.
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From AI research to production infrastructure
Partnerships with labs inform our methods; our deliverables are production deployments, monitoring, and upskilling your team. Every technique has to survive real latency, security, and maintenance constraints before we recommend it.
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Your data is your moat
The companies winning with AI aren't the ones with the best models - they're the ones with the best data. On-premise infrastructure means you can train on proprietary data without ever exposing it. That's a competitive advantage no API can match.
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Open source is ready
Llama 3, Mistral, DeepSeek - open-source models are now within striking distance of GPT-4 for most business tasks. The gap is closing fast. The question isn't whether to go open source - it's when.
Ready to own your AI future?
Let's assess your AI readiness and map out a path to independence. Whether you're starting from zero or escaping API dependency, we'll show you what's possible.
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