3× recall ↑
Build Pipelines
Audit a RAG pipeline end-to-end
NEO inspects retrieval, prompts, and model calls, finds zero-context failures, and delivers a report with fixed thresholds.
View walkthroughUse cases
Real projects built by NEO — from LLM benchmarks to agent swarms. Pick a workflow below to browse, or start with a featured use case.
Build Pipelines
NEO inspects retrieval, prompts, and model calls, finds zero-context failures, and delivers a report with fixed thresholds.
View walkthroughEvaluate & Benchmark
Run structured quality, latency, and cost comparisons across providers automatically. Pick models with evidence, not intuition.
View walkthroughBuild Agents
NEO wires tool boundaries, shared memory, and retry logic so your agent swarm stays reliable as requirements change.
View walkthroughMulti-agent swarms, autonomous research agents, tool-use orchestration, self-healing pipelines, and memory management.
LoRA adapters, supervised fine-tuning, knowledge distillation, RLHF, and quantization, from raw data to deployment-ready weights.
Model comparison, consistency testing, latency profiling, and automated eval suites across providers and hardware.
GGUF quantization, batch inference, edge deployment, GPU monitoring, and CPU-optimized serving for production workloads.
Prompt injection defense, adversarial red-teaming, bias auditing, model watermarking, and output guardrails.
RAG systems, multimodal OCR, voice translation, drug discovery, time-series forecasting, and document intelligence.
Code analysis agents, schema inference, test generation, API scaffolding, no-code agent builders, and CLI tools.
Agents with brittle tool calls. Prompts that need another pass. Evals before you trust a model swap. NEO lives in VS Code or Cursor and helps you turn that work into real code and runs, so you iterate on behavior, not boilerplate.
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