How monday.com Turns AI Agents Into Real Teammates for End Users with Tavily

About monday.com

For more than a decade, monday.com has transformed how businesses run, helping define and lead the work management category by bringing teams, data, and processes together on one flexible platform.

⁠In May 2026, monday.com relaunched with a new vision: an AI workspace built for an AI-native era. At the center are monday Agents, where anyone on a team can create AI agents that understand context, use tools, and take action inside the workflows they already run. They’re not assistants that answer questions on the side, but teammates that do real work.

The problem: an agent can't act on what it can't see

monday.com Agents could already decipher rich context about what was happening inside a business. They had visibility into projects, customers, tasks, documents, and workflows. But, across monday.com's AI experiences, agents also needed to reach outside the platform as part of everyday workflows, allowing customers to research a competitor, enrich a lead, verify a fact, and understand the latest market news.

So, for monday.com Agents to become true teammates, they needed reliable web search. That's when monday.com turned to Tavily.

Why Tavily

The decision to partner with Tavily was a strategic choice about where to focus engineering investment. Because retrieval infrastructure requires continuous investment in coverage, freshness, and relevance as the web changes, the monday.com team chose to source that layer to Tavily, who specializes in real-time web retrieval, while accelerating the agent experience (workflow logic, permissions, and tool orchestration).Three things gave the team confidence in that decision.

1. Production track record. monday.com first ran Tavily inside its Sidekick and AI Blocks products, where it proved reliable retrievals across the different agentic surfaces. This is also proving to be the case in monday Agent, where in production today, 99.8% of those retrieval calls complete without failure.
2. Range across use cases. Sidekick and AI Blocks serve different user needs and workflows. Tavily performed consistently across both, giving the team confidence in its diversity and strengths, from structured internal workflows to open-ended external research. One integration now serves multiple monday.com AI products.
3. Model-agnostic by design. Tavily is not tied to a single model's native search. This architectural separation also preserves monday.com's flexibility to evolve its agent stack and retrieval layer over time as the AI ecosystem matures.

The solution: giving agents access to the web

Inside monday Agents, web search is now a capability agents can call when a workflow requires external signals in addition to internal data. Agents start with structured internal data from monday.com objects like boards, dashboards, and CRM records, then use Tavily to bring in outside information when needed.

This allows agents to move from understanding internal workflows to acting with awareness of what is happening in the broader world.

As Dor explains, "It's not only about the intelligence we provide to the agent. It's also about the context, tools, identity, and permissions we give it."

Results: agents that act as true teammates

Today, more than one-third of classified calls are tied to either news monitoring or contact enrichment. Both are inherently recurring workflows, which means retrieval is not happening occasionally. It's happening continuously, as part of systems that depend on freshness and correctness.

When an agent makes an outside call, 99.7% of web searches return at least one helpful result, and end users perform retrieval at production scale with a 0.2% failure rate.

monday.com end users are leveraging Tavily for:

• Company and competitor research, where agents surface pricing changes, product launches, funding events, and market shifts that are not captured in internal systems
• Contact enrichment, where agents find external data that keeps people and company records current as roles and businesses change
• News monitoring, where agents continuously track external developments so teams can respond as events unfold
• Content and fact research, where source-backed search results are used to validate information before it's used in outputs or decisions

monday.com has built for what's next

As agents become more embedded in day-to-day work, access to reliable, real-time external information stops being an enhancement and becomes a requirement.

With Tavily's real-time search layer plugged in, monday.com's Agents can pull the live context they need, turning them from tools that answer into teammates that get work done.