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AgentOps Workflow Control Plane
50 Signals+2

AgentOps Workflow Control Plane

A control plane for teams to build, deploy, evaluate, and monitor LLM agents and RAG workflows across internal systems.

Added Jun 6, 2026

AI Infrastructure
LLMOps
Workflow Automation
Opportunity score

Medium opportunity (63%)

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The Problem

Companies are hiring engineers to stitch together LLMs, retrieval systems, agent frameworks, tool calls, prompt engineering, and internal data integrations. The repeated need for orchestration, evaluation, observability, and deployment suggests teams struggle to move LLM workflows from prototypes into reliable production systems.

Potential Solution

AgentOps Workflow Control Plane provides a managed workspace for designing agentic workflows, connecting internal data sources, configuring RAG pipelines, testing prompts and tool-call behavior, and tracking production performance. It focuses on deployment readiness with evaluation suites, observability, versioning, and framework integrations for LangChain, LlamaIndex, and custom agents.

Why Now?

Job postings across Salesforce, GitLab, Apple, BillionToOne, Turing Labs, Instawork, Lemlist, and Sephora show enterprises are actively operationalizing LLM agents rather than merely experimenting. As agent frameworks proliferate, teams need infrastructure that standardizes orchestration, evaluation, and monitoring.

Market validation
Search demand

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Competition
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Showing 1-20 of 50 signals

Job adsSep 23, 2026
kristal-advisors-sg-pte-ltd-201711235e
AI Engineer

• Build and ship production applications powered by large language models, including retrieval-augmented generation (RAG) systems over our internal documents, policies, and client communications. • Design and build AI agent workflows using frameworks such as LangGraph or LangChain, including tool calling, multi-step orchestration, and memory.

Job adsSep 23, 2026
micron-semiconductor-asia-operations-pte-ltd-201815216z
Member of Technical Staff - Agentic AI Architect

Implement Agentic frameworks to orchestrate LLM interactions with internal APIs, databases, and software tools. Build and maintain agent evaluation harnesses to benchmark agent accuracy, reliability, and task success across complex, multi-step workflows.

Job adsSep 19, 2026
regask-pte-ltd-201824105d
Senior Applied AI Engineer

You will own outcomes end to end. That means the agent, the evaluation harness that proves it works, and the surface our customers actually touch. Design and implement agent workflows using LangGraph/LangChain, with a strong focus on orchestration, observability and debugging.

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