Auctor is a pre-product-market-fit startup (founded 2025, 11–50 people) building agentic workflows for professional services and systems integrators. The tech stack is modern-web heavy (Next.js, TypeScript, Python) with enterprise connectors (Jira, Confluence, SharePoint, HubSpot), signaling a focus on retrieving and acting on messy, fragmented client data. Active projects confirm this: LLM evaluation, retrieval pipelines over enterprise datasets, AI agent configuration, and custom integrations dominate the roadmap. The hiring mix is engineering-forward (4 engineers vs. 1 sales) with decelerating velocity, typical of early-stage companies stabilizing after initial hiring and pivoting go-to-market strategy.
Auctor builds software that automates implementation workflows for professional services firms and systems integrators—teams that deploy and configure enterprise software for clients. The product surfaces as an agentic operating system: it ingests fragmented project data (from Jira, Confluence, SharePoint), retrieves context from unstructured documentation, and uses LLMs to automate decision-making and documentation tasks. The company is actively building retrieval pipelines, agent configuration interfaces, and custom integrations for strategic customers. Headquartered in New York with a team skewed toward engineering and product, Auctor is currently defining its go-to-market strategy and establishing relationships with systems integrators.
Next.js, TypeScript, Python, with integrations into Jira, Confluence, SharePoint, and HubSpot. The stack supports retrieval pipelines, LLM evaluation, and agentic workflow orchestration.
Agentic workflows, LLM evaluation, retrieval pipelines over enterprise documents, AI agent configuration for customer workflows, custom integrations, and go-to-market strategy foundation.
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