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Hey HN, I've been building SimplAI for the past several months — it's a platform for
building, testing, and deploying LLM-powered agents and multi-step workflows. The problem I kept running into: spinning up an AI agent pipeline means
stitching together prompt management, tool calling, memory, evals, and
deployment — often from scratch every time. SimplAI tries to be the layer
that handles all of that so you can focus on what your agent actually does. What it does:
- Visual + code-first workflow builder for chaining LLM calls, tools, and APIs
- Built-in prompt versioning and A/B testing
- Supports multiple LLM providers (OpenAI, Anthropic, Gemini, etc.)
- Evaluation and observability built in, not bolted on
- Deploy agents as APIs in one click It's not trying to be LangChain or LlamaIndex — the focus is on speed to
production and giving non-ML engineers a sane path forward. Happy to answer questions about the architecture, design decisions, or
anything else. Critical feedback especially welcome. |