AI API pricing is unpredictable.
Token-based billing creates uncertainty for developers, startups, agentic applications and enterprise teams.
Investors
Fixed-price AI access for frontier-scale model infrastructure.
Gamma AI is developing Gamma, a 100B+ open multimodal model family and a cost-aware platform for chat, API access, model improvement and research workflows.
Investment thesis
The next advantage is not only pretraining.
Open-weight models are powerful but fragmented.
Quality, deployment reliability and cost control remain uneven across the ecosystem.
Model assembly is becoming infrastructure.
Durable advantage comes from verification, distillation, routing, cost control and product packaging.
Gamma combines research methods with fixed-price access.
Proprietary improvement infrastructure is paired with a subscription API model designed for predictable usage.
What we are building
A model family, API product and research pipeline.
Gamma Models
100B+ Alpha, distilled family, and long-term 1T+ sparse MoE target.
Gamma API
Chat and OpenAI-compatible API under fixed subscription and fair-use throughput.
Gamma Research
Gamma AI Learn-Training and EvoStream research pipeline, prepared for technical publications and arXiv.
Technology stack
Layered model-improvement infrastructure.
Model Construction
EvoStream: adaptive model fusion, streaming merge, architecture bridge, MoE-aware merge and activation-guided search.
Model Improvement
Gamma AI Learn-Training: Verifier-First Learning, Jordan Loop, SafeTrain, Hard-Negative Mining, Adapter-Centric Evolution and UltraContext Reasoning.
Data Factory
Semanta: synthetic data, committee verification, gold builders, dataset generation and teacher-student pipelines.
Search Intelligence
AlphaZero-inspired self-play, selective deep search, pruning, value models and reasoning-state caching.
More than a model
A repeatable model-improvement factory.
Gamma AI is not building a single static model. New open-weight models can enter the pipeline, then be audited, routed, merged, bridged, distilled or used as teachers.
Evaluation and verification gates are designed to prevent degradation, while smaller models can be distilled from larger Gamma systems. The infrastructure is designed around cost control from the beginning.
Roadmap
From closed alpha to frontier-scale systems.
Gamma 100B+ Alpha
Internal assembly, evaluation and closed testing.
Gamma API Beta
Chat, API keys, developer access and cost telemetry.
Gamma Family
70B / 30B / 14B / 8B / 4B distilled models.
Gamma 1T+
Sparse MoE monolith, expert specialization and multi-teacher distillation.
Research Publications
Gamma AI Learn-Training, EvoStream, Semanta and search-driven intelligence papers.
Business model
Fixed-price access rather than unpredictable token bills.
Gamma is designed around fair-use throughput, normal-use predictability and no hard monthly token anxiety.
Commercial tiers are planned for founders, builders, scale teams and enterprise users, with anti-abuse controls, no resale and no dataset farming.
What we are seeking
Capital, compute and design partnerships.
Compute partners
Training, inference, orchestration and cost optimization.
Strategic investors
Long-term capital aligned with model infrastructure and research.
Research collaborators
Evaluation, training methods, synthetic data and search-driven intelligence.
Design partners
Developers and agentic app teams testing Gamma API workflows.
Enterprise pilots
Predictable AI access, controlled deployment and custom integration.
Use of funds: compute, model R&D, engineering, dataset generation, evaluation and safety, API infrastructure, legal/licensing and research publications.
Investor Pack
Available on request.
Gamma is our model. EvoStream is one engine. Gamma AI is the system behind it.