Small Language Models & On-Device AI
Compact, efficient models that run at the edge — low latency, full privacy.
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Compact, efficient models that run at the edge — low latency, full privacy.
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Privacy-safe training data at scale — augment, balance, and unblock ML.
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Benchmark, stress-test and adversarially probe models before they ship.
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Cooperating agents with tool-calling, handoff and MCP/A2A protocols.
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Event processing and instant anomaly detection on Kafka/Flink pipelines.
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Enterprise knowledge graphs and graph-based retrieval for real reasoning.
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Token cost tracking, tracing and continuous evaluation in production.
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Embeddings, vector databases and semantic search at production scale.
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Real-time speech-to-speech agents and intelligent voice interfaces.
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Risk classification, documentation and conformity for EU AI regulation.
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