SLMs process requests in milliseconds, not seconds. Your team gets instant, more accurate answers, and your infrastructure costs stay predictable.
When trained on your specific data and use cases, a 1B parameter model outperforms GPT-5 on your business tasks. Why? It's not distracted by trying to know everything.
Small enough to deploy on your own servers. No API calls, no data leaving your environment, no compliance concerns. Complete control over your AI.
Major health insurer struggled with complex coverage questions. Generic AI gave wrong answers 40% of the time, risking compliance violations. We deployed a specialized model trained only on their policies. Now customers get instant, accurate coverage recommendations — from "preventive care options" to "pre-existing condition coverage." Impact: 34% more conversions, 68% fewer calls, zero compliance issues. Deployed in 5 weeks, runs entirely on-premise.
Regional bank wanted to stop wasting time on untargeted campaigns. Manual analysis took days, generic AI didn't understand their specific customer base.Now sales teams just ask: "Find SME clients with good payment history who might need working capital" or "Which dormant accounts are worth reactivating?" Gets answers in 2 seconds.Impact: Campaign ROI up, analysis time from days to seconds, runs entirely on bank's servers.
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Up to 95% of AML alerts are false positives. Learn how small language models reduce false positive rates by 40-70% while running on your own infrastructure.
