{"slug": "show-hn-seclai-see-what-your-llm-agents-are-doing-in-production", "title": "Show HN: Seclai – See what your LLM agents are doing in production", "summary": "Seclai launched on Show HN as production infrastructure for LLM agents, combining step-level observability, natural-language governance policies with flag and block thresholds, eval sets that run identically locally, in CI and in production, and switching across 200+ models from providers including Anthropic, OpenAI, Google and Meta. The platform exposes every agent as an HTTP endpoint that returns run_id, output, trace and cost on the same call, with SDKs for Python, JavaScript, Go and C#, and includes an ML-based prompt scanner that screens agent input, saved source content and webhook responses for prompt injection. Seclai positions the offering for teams that must answer for what they ship, bundling retries with fallback models, persistent memory, RAG ingestion from RSS feeds, websites, file uploads and REST APIs, and per-model, per-agent and per-step cost tracking.", "body_md": "Seclai is the production infrastructure for AI applications. Orchestrate workflows, evaluate outputs, enforce governance, and switch between 200+ models — visually or in code.\n\nLead enrichmentcompletedsample_and_flagToday, 09:272.9s3/35.20—1\n\nWhy Seclai\n\nBuilt for teams who have to answer for what they ship.\n\nEvery piece of a production LLM system, unified under one runtime. No orchestration stack to assemble.\n\n01 / Observability\n\nStep-level traces\n\nEvery step in every run with status, latency, credits, and governance. Replay any trace from your dashboard.\n\nStep\n\nStatus\n\nDur.\n\nCred.\n\nGov\n\nInput Scan\n\nDone\n\n86ms\n\n—\n\n✓\n\nEvaluate response\n\nDone\n\n1.61s\n\n4.30\n\n✓\n\n02 / Governance\n\nNatural-language policies\n\nWrite what you want screened in plain English. Every input and output is graded with flag and block thresholds you set.\n\nContent Safety\n\nFast\n\nFlag≥0.50 Block≥0.80\n\nPII Protection\n\nFast\n\nFlag≥0.50 Block≥0.80\n\nForbidden Topics\n\nFast\n\nFlag≥0.60 Block≥0.85\n\n03 / Evals\n\nSame runtime for tests\n\nDefine eval sets once. Run locally, in CI, and in production — with identical semantics.\n\nfaithfulness: 0.94 ↑\n\n04 / Parity\n\nLocal = production\n\nWhat you build and test is what runs in production. Clone any agent and it behaves identically, with nothing to re-verify or debug.\n\nsupport-agent\n\n→\n\nsupport-agent-prod\n\n✓ workflow\n\n✓ models\n\n✓ policies\n\n✓ evals\n\n05 / Models\n\nSwap models, not code\n\n200+ models from every major provider, switchable at agent step.\n\n06 / Deploy\n\nRun from your app\n\nEvery agent has an HTTP endpoint. POST an input and you get the output, trace, cost, and governance verdict back on the same call. SDKs for Python, JavaScript, Go, and C#.\n\nPOST /agents/{id}/runs\n\nX-API-Key: ••••\n\n{ \"input\": ... }\n\n→ run_id, output, trace, cost\n\nHow it works\n\nThree Steps to Your First Agent\n\nGo from content source to deployed agent in minutes.\n\n01\n\nAdd a content source\n\nEnter a URL or upload a file. Seclai auto-detects the type and sets up syncing.\n\n02\n\nCreate a knowledge base\n\nYour content is indexed into a vector database automatically for retrieval.\n\n03\n\nBuild an agent\n\nWire your knowledge base into a workflow with the visual builder, then deploy.\n\nAlso included\n\nAnd everything else production demands.\n\nBuilt-in so you don't have to build it yourself.\n\nAI Assistant\n\nDescribe what you need and the assistant configures your agent, sources, and policies. No guessing required.\n\nResilience & Retries\n\nAuto-retry on bad output with fallback models. Structured output validation ensures quality responses.\n\nMemory\n\nPersistent conversation and general memory banks. Agents remember context across sessions.\n\nCost Management\n\nPer-model, per-agent, per-step cost tracking. Credit-based pricing with budget controls and alerts.\n\nSee It In Action\n\nThe full platform, end to end.\n\nWatch a walkthrough from content ingestion to a production-ready agent with all eight pillars working together.\n\nFrequently Asked Questions\n\nWhat do you mean by 'everything around the LLM call'?\n\nEvery production LLM feature needs more than just the API call. You need retries when output is malformed, evaluation to catch quality regressions, observability to debug multi-step pipelines, governance to screen content, cost tracking per model and user, RAG infrastructure, and persistent memory. Seclai provides all of this out of the box.\n\nHow does model portability work?\n\nSelect any of 200+ models from Anthropic, OpenAI, Google, Meta, and others from a dropdown. Your workflows, prompts, and data stay the same. You can also use each provider's native syntax for advanced features.\n\nWhat sources can I connect for RAG?\n\nRSS feeds, websites, file uploads (PDFs, docs, audio, video), and REST APIs. Content is automatically chunked, embedded, and kept in sync.\n\nHow does Seclai protect against prompt injection?\n\nSeclai includes a fast ML-based prompt scanner that screens all input to agents, all content saved to sources, and all webhook responses. The scanner blocks prompt injection attacks in real time before they reach any LLM, with zero LLM cost. This works alongside governance policies which screen outputs after the fact.\n\nHow does governance screening work?\n\nDefine safety, privacy, and compliance policies. Seclai automatically evaluates agent outputs and source content against these policies, flagging or blocking content before it reaches your users. Governance operates after the fact — the prompt scanner handles real-time input protection.\n\nIs there a free trial?\n\nYes! New accounts get a free trial with full feature access and credits to get started. The free trial is limited to one per person. Most accounts that sign up with a social login can start without a credit card. All eight production pillars are included.", "url": "https://wpnews.pro/news/show-hn-seclai-see-what-your-llm-agents-are-doing-in-production", "canonical_source": "https://seclai.com/", "published_at": "2026-10-20 15:00:10+00:00", "updated_at": "2026-10-20 15:17:11.070269+00:00", "lang": "en", "topics": ["ai-agents", "large-language-models", "mlops", "ai-safety", "developer-tools"], "entities": ["Seclai", "Anthropic", "OpenAI", "Google", "Meta"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/show-hn-seclai-see-what-your-llm-agents-are-doing-in-production", "markdown": "https://wpnews.pro/news/show-hn-seclai-see-what-your-llm-agents-are-doing-in-production.md", "text": "https://wpnews.pro/news/show-hn-seclai-see-what-your-llm-agents-are-doing-in-production.txt", "jsonld": "https://wpnews.pro/news/show-hn-seclai-see-what-your-llm-agents-are-doing-in-production.jsonld"}}