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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.
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Small, instant, invisible.
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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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Decagon voice AI cost fell nearly 6x per turn versus closed models such as GPT-5 mini, with reported p95 model latency below 400 ms.
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Boosted.ai Cut a Nearly $1 Million Model Cost by 90%
Conscious Engines
The Boosted.ai smaller model reduced a nearly $1M annual general LLM cost by a reported 90% while maintaining finance-task quality.
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StudyFetch specialized speech AI cut its largest inference workload cost roughly 10x after a managed transcription bill reached six figures monthly.
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CarbonTrail AI cost reduction reached a reported 88% versus comparable GPT-4 with embeddings, with 87% faster processing and better confidence.
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Forethought Cut Model-Serving Cost Up to 80% by Matching Infrastructure to the Workload
Conscious Engines
Forethought task-specific models used shared and serverless inference to cut relevant serving costs up to 66% and small-classifier cloud costs about 80%.
case study
[Case Study] From ₹20 Lakh to ₹3 Lakh a Month: Rebuilding Enterprise RAG for Real Estate
Conscious Engines
How a large real-estate group rebuilt enterprise RAG with domain retrieval and an on-premise SLM, reducing its reported monthly cost from ₹20 lakh to ₹3 lakh.
case study
[Case Study] The $53.9 Million Contact-Center Case: TELUS and Agentic AI
Conscious Engines
How TELUS used Google Cloud AI to analyze more than 22 million calls annually, automate 30% of traffic, and report $53.9 million in annual savings.