38 Signals

AgentOps Evaluation Control Plane

A SaaS platform for designing, testing, deploying, and monitoring multi-agent AI workflows built with frameworks like LangGraph, CrewAI, AutoGen, and custom orchestration layers.

Added May 29, 2026

AI Developer Tools

Agent Operations

LLM Evaluation

Opportunity score

Medium opportunity (73%)

Loading score details

The Problem

Companies are hiring specialists to build production AI agents, tune prompts, orchestrate multi-agent workflows, and keep agent behavior reliable after deployment. The repeated need for evaluation frameworks, A/B prompt testing, error recovery, and ongoing operations suggests teams struggle to move agents from prototype to dependable production systems.

Potential Solution

The product provides a control plane for agent engineering teams: workflow configuration, prompt versioning, A/B testing, behavior tuning, evaluation suites, deployment checks, and production monitoring. It integrates with common agent frameworks and gives teams a shared operational layer for reliability, testing, and lifecycle management.

Why Now?

Job postings show agentic AI moving from experimentation into production ownership, with companies explicitly hiring for full-lifecycle agent architecture, testing, deployment, and operations. As more businesses adopt multi-agent systems, the need for tooling around reliability and evaluation becomes urgent.

Market validation

Search demand

Trend snapshot pending

Competition (0)

No matched competitors yet

Showing 1-20 of 38 signals

Job adsSep 12, 2026

klaviyo

Lead Engineer, Applied AI (Customer Agent)

Experience working on a multi-tenant agent platform at production scale, where external customers configure their own agent behavior on shared infrastructure. A track record with production evaluation systems, AI observability, or human-in-the-loop workflows for LLM-powered products.

Job adsSep 3, 2026

amazon

Software Development Engineer , Adaptive Search Relevance

- Build and scale a multi-agent orchestration platform that autonomously executes research workflows — from hypothesis generation and experiment design through training, evaluation, and production deployment — with fault tolerance, cost controls, and security compliance

Job adsSep 2, 2026

dell

Senior Analyst, Agentic AI Engineer

Design, develop, test, and deploy AI-powered agents and workflows using large language models, retrieval systems, and enterprise data sources. Define evaluation frameworks, monitor production performance, troubleshoot issues, and continuously improve solution accuracy and adoption.

RedditAug 31, 2026

r/AI_Agents

Production-Grade Agentic AI Platforms in 2026 — I Tested the Landscape, Here’s My Shortlist

I’ve been researching agentic AI platforms for production use in 2026, and one thing became pretty clear: **“Can build an AI agent” ≠ “Can run AI agents in production.”** There are now dozens of frameworks, agent builders, automation platforms, and enterprise AI platforms. So I narrowed the evaluation down to what actually matters when you're moving beyond a PoC. # What I evaluated * Multi-agent orchestration * Stateful / long-running workflows * Human-in-the-loop approvals * RAG & enterprise data integration * Evaluation & testing * Tracing / observability * Governance & access controls * Deployment flexibility * Integrations * Production scalability * Ease of moving from PoC → production # My 2026 shortlist **1. LangGraph** Still one of my top choices when engineering control is the priority. The graph/state-based approach gives developers a lot of control over complex workflows, branching, persistence and human-in-the-loop execution. **Best for:** engineering-heavy teams building highly customized agent systems. **Downside:** you're still responsible for a lot of the surrounding production infrastructure. **2. Microsoft Agent Framework** Very interesting option for organizations already heavily invested in Microsoft/Azure. The ecosystem integration, enterprise identity, governance and Microsoft stack make it compelling for large organizations. **Best for:** Microsoft-centric enterprises. **Downside:** less attractive if you want to remain cloud/vendor agnostic. **3. SimplAI** This was probably the most interesting platform I came across when looking specifically at **enterprise agent operations rather than just agent development**. What stood out: * Visual agent + workflow building * Multi-agent orchestration * Agentic RAG * 300+ data connectors * Built-in evaluation * Tracing/observability * Human approval workflows * Governance * Multi-model support *...

Job adsAug 20, 2026

tiktok

Machine Learning Engineer Intern (E-Commerce Supply Chain & Logistics-LLM/Agent) - 2027 Start (PhD)

- Support agent architecture, engineering, evaluation, and evolution work, including runtime orchestration, memory and state management, model / tool routing, permission-safe execution, observability, benchmark and Golden Set evaluation, bad case attribution, regression testing, online feedback loops, and continuous improvement of context, skills, workflows, and model behavior.

Unlock 35 more signals

Go beyond the grade and inspect the evidence behind this opportunity.

Job ads

See which companies and roles are investing in this problem.

34 more

Reddit discussions

See the original problems, requests, and conversations.

1 more

Launch signals

Review adjacent products and evidence of competition.

9 more