case study
StudyFetch AI cost reduction reached roughly 10x on its largest workload. See the architecture, verified metrics and enterprise replication plan.
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Small, instant, invisible.
Company
You don’t need a frontier model for every task
We build small, specialized AI models so that intelligence can be fast, affordable, and invisible — embedded in the products that already do the work.
Conscious Engines
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Research, engineering write-ups, and the thinking behind the models we build. We publish what worked and what didn't.
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Cut the AI Bill Before It Scales: 12 Production Levers That Work
Conscious Engines
Enterprise AI cost reduction requires more than cheaper tokens. Use 12 production levers backed by StudyFetch, Pinterest, Observe.AI and others.
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Build an AI FinOps system that controls model, agent, RAG, speech and GPU costs using attribution, budgets, forecasts and cost per accepted outcome.
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Build vs Buy Is the Wrong Question for Enterprise AI
Conscious Engines
Build vs buy enterprise AI using evidence from six deployments. Learn when to buy software, commission bespoke AI or build internally.
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The Bespoke AI Business Case: From Token Costs to Operating Leverage
Conscious Engines
Build a bespoke enterprise AI business case using TCO, cost per accepted outcome, risk-adjusted ROI and evidence from real companies.
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Frontier Models Are Becoming the Teacher, Not the Runtime
Conscious Engines
See 13 companies replacing frontier AI models in production, the savings they report, the tradeoffs they found and the architectures that worked.
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Replit intelligent model routing delivered the same tested output quality at 65% lower cost. See the enterprise architecture and caveats.
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Meta Sends 85% of This AI Workload Through Rules, Not an LLM
Conscious Engines
Meta deterministic AI routing sends about 85% of asset classifications through rules and reserves an LLM path with roughly 400x compute cost.
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Siemens AI cost reduction reached 70% after switching global search to Nova 2 Lite, alongside 300% faster search and 11% higher satisfaction.
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Sully.ai open-source models cut reported inference cost over 90% and median latency 65% after clinical agents moved away from closed services.