Airtable, the no-code platform powering workflows for over 500,000 organizations including 80% of the Fortune 100, has unveiled Superagent, its first standalone product in 13 years. Launched at superagent.com, the tool marks a bold pivot toward multi-agent AI coordination, built directly on the company’s acquisition of DeepSky last fall. Founder and CEO Howie Liu positions it as a shift from single-threaded AI chats to parallel, collaborative intelligence that executes complex tasks autonomously.

Superagent deploys a central coordinating agent to break down user prompts into parallel subtasks handled by specialized agents. For instance, evaluating Google as a three-year investment triggers agents for financial analysis, competitive positioning, management review, and news scanning. Outputs consolidate into interactive visualizations: filterable matrices, expandable detail cards, and positioning maps, ready for boardroom use. “Multi-agent coordination is the defining architecture of today. We’re moving AI from single-threaded chat to parallel, collaborative intelligence,” Liu wrote in the Built In coverage of the launch.

From DeepSky Roots to Standalone Powerhouse

The product stems from Airtable’s October 2025 acquisition of DeepSky, formerly Gradient, an AI agent startup that raised $40 million. DeepSky specialized in autonomous research for investment reports, market assessments, and strategic insights, popular among Stanford MBAs and investors. Its founding team—Chris Chang, Forrest Moret, and Mark Huang—joined Airtable with 12 staffers, now helming Superagent semi-independently, as detailed in Upstarts Media. Chang will report directly to Liu, preserving DeepSky’s self-service model while integrating with Airtable bases.

This deal, Airtable’s largest to date with terms undisclosed, accelerates the company’s AI-native transformation. DeepSky’s superagent complemented Airtable’s Omni app builder: DeepSky for research and strategy, Omni for execution on structured data. “DeepSky brings the brains and legs: multi-step research, quantitative analysis, retrieval, planning, and tool use across the web and internal systems,” Chang explained in his Substack post.

Valuation Reset Fuels Aggressive AI Push

Airtable’s move comes amid a valuation drop from $11.7 billion in 2021 to about $4 billion on secondary markets. Yet with $700 million cash from $1.4 billion raised and positive cash flow, Liu views it as an advantage. “The valuation collapse affected investor returns and employee stock options but didn’t undermine the business itself,” he told Yahoo Tech. Lower valuations aid recruiting with richer equity upside, enabling “wartime” focus on adaptation over defense.

Employing over 700, Airtable serves mission-critical operations without new funding needs. Liu frames Superagent as potential to eclipse the core platform long-term, though Airtable remains larger near-term. The launch coincides with CTO David Azose’s hiring from OpenAI, where he led ChatGPT business products, bolstering engineering for agentic frameworks.

Technical Edge in Agent Orchestration

Unlike sequential LLM chats, Superagent’s coordinator plans, deploys specialists, synthesizes, and delivers polished artifacts—reports, slides, or sites. It plans work across pipelines, generates insights flowing into structured data, and automates intelligence at scale. Future integrations allow invocation from Airtable bases for dynamic research, per the official Airtable announcement.

Airtable’s prior AI builds—like agentic frameworks for Omni and Field Agents—handled dynamic decisions, internet fetches, and base analysis. Superagent extends this to enterprise-grade multi-agent systems, addressing limitations of early features. “Agents don’t just help you work. They do the work,” Liu emphasized.

Enterprise Use Cases and Integration Path

Targeted at complex queries like competitor analysis, market opportunities, or strategic decisions, Superagent turns prompts into exhaustive, fact-checked deliverables. Users in finance, strategy, and operations gain tools for investment evaluations or positioning maps without manual synthesis. Early adopters leverage it for boardroom-ready outputs, with Airtable planning deeper data source expansions.

Bi-directional synergy shines: Superagent pulls from Airtable for structured inputs, while outputs feed back into apps for tracking. This loop shifts from manual entry to autonomous updates, unlocking market intelligence systems. As TipRanks notes, it diversifies revenue while future-proofing against AI commoditization.

Competitive Positioning Amid AI Frenzy

In a crowded field, Superagent differentiates via Airtable’s no-code moat—democratizing app-building now extends to agent orchestration. Rivals like major productivity suites push agents, but Airtable’s 500,000-org base and cash reserves enable scaled experimentation. Liu bets on coordination over single-model smarts, potentially resonating in enterprise where visibility and execution matter.

Challenges persist: proving “true autonomous agents” over LLM workflows, amid intense competition. Yet with DeepSky’s track record in quantitative reports and Airtable’s governance, Superagent targets buyers needing reliable, structured intelligence. Live now, it signals Airtable’s multi-product era, blending databases with AI autonomy.