From enterprise teams investing in model training to research labs pushing the frontier — there is a plan built for your scale.
For research institutions, engineering teams, and organizations evaluating Model Surgery. Full access to the core pipeline.
No credit card. Apply via contact form.
For AI startups and product teams. Unlimited concepts, commercial license, priority support, and advanced rank-k surgery.
Notify me when Growth launches.
For large organizations integrating Model Surgery into production AI pipelines. Custom infrastructure, dedicated support, and SLA guarantees.
One training run costs $200,000 on average. One Model Surgery transplant costs $0. Any plan pays for itself the first time you use it.
Model Surgery runs on standard hardware — no specialized infrastructure required. Concept mapping completes on CPU in under one second. The transplant operation loads models into memory but requires no expensive forward passes or training loops. For production deployments at scale, GPU acceleration is available but not mandatory.
Any transformer architecture with MLP layers — GPT-2, LLaMA, Mistral, Falcon, Qwen, Phi, and the full HuggingFace ecosystem. The pipeline auto-detects architecture and adapts accordingly. The technology scales with model size: larger models have richer internal representations, which means more precise concept mapping and higher-fidelity transplants. Enterprise-scale models see the strongest results.
After transplanting a concept, we run an independent post-graft probe: we fast-map the same concept in the target model and compare the geometric direction to the donor's map via cosine similarity. 0.917 means the target model now stores the concept in 91.7% the same direction as the donor — confirmed causal transfer, not noise.
Our interference detection system scans every layer before any weight is touched. If a concept collision above 0.7 cosine similarity is detected, the system issues a CAUTION or ABORT rating and prevents the surgery. No write happens without verification.
Simple concepts (a single word, a fact) live in a single weight-space direction — rank-1. Complex capabilities like a language, a reasoning style, or a domain of expertise require multiple simultaneous directions — rank-k. Higher k = richer, more complete transplant. Research tier supports up to k=4; Growth to k=32.
Yes — patent applications are filed and pending. The specific combination of gradient-SVD concept addressing, orthogonal Procrustes cross-model alignment, and rank-k conjugation transplant as a unified system is our novel contribution. Provisional filing complete as of 2026.
We are in a private beta, working with select teams to refine the enterprise integration experience. Growth pricing will be announced Q2 2026. Join the waitlist to be notified first.
Submit a request through our contact page. Our team reviews every application — we are onboarding teams with high-impact use cases. Research institutions and funded organizations are prioritized.
Join the private beta. Be among the first teams to transplant neural knowledge instead of retraining it.