For sales engineers and proposal teams buried in RFPs, 1up is an AI knowledge automation platform that reads your internal docs and auto-answers sales and security questionnaires, cutting the manual research out of every deal.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
1up is working to become the answer layer for sales engineering and security review, an AI system that reads a company's own documentation to auto-complete the RFPs, security questionnaires, and procurement portals (OneTrust, CyberGRX, and Coupa among them) that slow enterprise deals in legal and infosec. Public conversation about deal-desk and questionnaire automation is still forming, and 1up's presence within it is early. What surfaces right now is largely its own product demonstrations, live walkthroughs of auto-answering compliance questionnaires and filling out procurement PDFs, rather than a broader practitioner debate about the category.
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Business Profile
1up was founded in 2021 by CEO George Avetisov and a team with a cybersecurity background, operating as a fully remote company based in New York. It has raised roughly $11M to date from investors including Upfront Ventures and Lightbank, funding growth from an early seed round through a 2025 Series A. The company has scaled to nearly 40 people and past 2 million AI-generated answers for customers such as WalkMe, Gladly, and Deliveroo, with trade press noting an unusually organic, meme-driven acquisition channel alongside its enterprise sales motion. Its answer engine runs on a vector-search backend rather than a generic LLM wrapper.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
1up's AI runs as an internal answer engine — surfacing grounded responses inside Slack and Teams, through a browser plugin that auto-fills web-based questionnaires, and via connectors into Confluence, Notion, and SharePoint. That integration layer pulls knowledge in rather than exposing it out: no public agent surfaces are on file yet, and the company hasn't published a developer-facing API, MCP server, SDK, or CLI for agents to call into its answer engine.
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