Solutions
Production-grade solutions that turn our open-source packages into deployable AI systems for specific business problems. Pick one, follow the DIY tutorial to see how it's done, download the examples and deploy them on your own infrastructure — for free — or tell us which ones you want customized and deployed.
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9 solutions
vllm-voice-agent-for-after-hours-small-business-support
Small service businesses miss after-hours calls, losing customers because they can't afford a 24/7 receptionist. Existing AI voice solutions require expensive cloud LLM APIs and send sensitive call data off-site.A self-hosted voice agent that answers after-hours calls using your own vLLM inference, with customizable workflows for appointment booking and FAQs.
vllm-observability-suite-for-smb-ai-operations
Small businesses running vLLM for AI inference struggle to monitor token usage, latency, and cost across multiple agents, leading to overspend and undetected performance regressions.Prebuilt observability stack with OpenTelemetry traces and dashboards for any AI agent using vLLM as the inference backend.
vllm-multi-agent-handoff-for-e-commerce-support-routing
E-commerce support teams hosting cost-effective vLLM models find it hard to coordinate multiple specialist agents; misrouted questions cause customer frustration and agent loops.Route customer queries across product, order, and returns agents hosted on vLLM, with compressed context handoff so no conversation gets lost.
vllm-ai-spend-control-for-smb-agent-workflows
Small businesses running agents on self‑hosted vLLM struggle to see aggregated LLM spend per customer, team, or use case. Without built‑in budgeting, a runaway prompt or misconfigured agent can balloon compute costs before anyone notices.Track, cap, and forecast LLM costs across all your agents powered by self‑hosted vLLM models, without slowing down responses.
vllm-agent-quality-gate-for-on-prem-smb-support-bots
An SMB running on‑premises support agents on vLLM lacks systematic regression testing after model updates or prompt changes. Manual conversation review is slow, and a bad deployment can degrade customer satisfaction before anyone notices.Automated regression testing for self‑hosted LLM agents, with CI gates that block deployment when support‑bot quality drops.
vllm-agent-mesh-for-e-commerce-order-management
Small online retailers manually handle repetitive customer queries about order status, shipping updates, and return policies. Delegating these tasks to a single LLM agent leads to context‑lost handoffs and inconsistent responses.A multi-agent system that handles order inquiries, shipment tracking, and returns for SMB e‑commerce stores, powered by a vLLM‑hosted model and orchestrated with REAA agent-mesh.
vllm-reliability-suite-for-netsuite-smb-financial-operations
SMBs using NetSuite need to classify transactions, detect anomalies, and enrich vendor data, but manual processes and unreliable point‑to‑point scripts cause data drift and missed insights.A durable sync pipeline that uses vLLM to enrich NetSuite records, with circuit breakers and idempotency so no transaction is lost or duplicated.
vllm-agent-eval-harness-for-fine-tuned-model-quality
SMBs that fine-tune open models locally lack a structured way to verify model quality before production, exposing them to regressions and failed customer interactions.Automated CI/CD-quality evaluations for locally-hosted fine-tuned LLMs using vLLM with LLM-as-judge and cost tracking.
vllm-security-guardrails-for-smb-api-gateways
SMBs exposing self-hosted vLLM APIs risk sensitive data leaks and misuse, but lack the security expertise to build custom guardrails.A drop-in API proxy that adds PII redaction, prompt injection defense, and content safety checks to any vLLM endpoint.