Your Head of AI knows the challenge: building reliable agents for customer support routing, sales lead scoring, or invoice processing shouldn't require expensive, over-powered foundation models. Yet most teams default to GPT-4 or Claude for every workflow because there's no better option.
Your Head of AI knows the challenge: building reliable agents for customer support routing, sales lead scoring, or invoice processing shouldn't require expensive, over-powered foundation models.
Yet most teams default to GPT-4 or Claude for every workflow because there's no better option.
Faster iteration cycles. Small models deploy in minutes, not hours. Test, tune, and ship rapidly.
Built for composition. Workflow SLMs integrate seamlessly into multi-model architectures, handling specialized tasks while larger models manage reasoning and orchestration.
Predictable performance. Purpose-trained models eliminate the inconsistency of prompt engineering against general-purpose LLMs.
Production economics. Run thousands of agents without crushing your inference budget.
