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Elastic Enterprise Search Beta Introduced

Elastic, the company behind Elasticsearch and the Elastic Stack, announced Elastic Enterprise Search, a new product that allows teams and organizations to search all the data scattered across the many productivity tools that power their everyday work life.

Across all industries, team members now enjoy access to an increasing number of purpose-built, cloud-based tools that are more focused and easier to use than ever before. These tools enable new forms of collaboration, faster execution, and an explosion of productivity for teams both large and small. This proliferation of content has created tremendous value, and it has also created a new opportunity: the chance to unify all information in one place and make it easily searchable from a single search box. Elastic Enterprise Search makes that possible, and it is now easier than ever before.

Elastic Enterprise Search is a consumer grade enterprise search solution. It provides easy to use, powerful search across all the tools used throughout your organization. It's a fast, scalable, and relevant search bar for your everyday work life.

Building on Elasticsearch’s proven relevance and scalability, we’ve designed a search experience that simply requires you to search the way you'd speak to a colleague, rapidly getting you to the document or answer you need. No need to configure any elaborate applications, traverse through complicated interfaces, or learn any strange conventions: Elastic Enterprise Search understands your intention and lets you remain focused on the task at hand.

Say farewell to the anxious days where multiple browser windows held hundreds of open tabs. Search all of your documents, pull requests, issues, tickets, contracts, spreadsheets — whatever it is, wherever they are, you have a single, organized gateway to getting things done.

Elastic Enterprise Search comes stock with cloud application connectors that get you started in just a few minutes. For this first beta release, we’ve focused on the cloud applications that are most commonly used in today’s modern organizations:

- Google Drive: Search over all of your docs, sheets, slides, and stored files.

- GitHub: Ingest all of your issues and pull requests.

- Salesforce: Sync accounts, contacts, leads, and opportunities.

- Dropbox: Index all of your images, static files, and documents.

- Custom Connector Framework: Sync data from any source, like an internal application, analytics engine, private communication channel, or knowledge base.

Enterprise Search provides privacy groups and tunable search relevance so that the right things are found by the right people. Assign each team member to a group: Engineering, Sales, Marketing, Design, Product, Leadership — whatever best fits your organization — and calibrate their sources’ relevance, based on their specific needs. Adjust the significance of GitHub for your Engineering team, Salesforce for your sales team, Dropbox for your design team; whatever fits. With granular access controls and group assignments, you can securely guide what will be found by individuals and groups. And what will not be found.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

Elastic Enterprise Search Beta Introduced

Elastic, the company behind Elasticsearch and the Elastic Stack, announced Elastic Enterprise Search, a new product that allows teams and organizations to search all the data scattered across the many productivity tools that power their everyday work life.

Across all industries, team members now enjoy access to an increasing number of purpose-built, cloud-based tools that are more focused and easier to use than ever before. These tools enable new forms of collaboration, faster execution, and an explosion of productivity for teams both large and small. This proliferation of content has created tremendous value, and it has also created a new opportunity: the chance to unify all information in one place and make it easily searchable from a single search box. Elastic Enterprise Search makes that possible, and it is now easier than ever before.

Elastic Enterprise Search is a consumer grade enterprise search solution. It provides easy to use, powerful search across all the tools used throughout your organization. It's a fast, scalable, and relevant search bar for your everyday work life.

Building on Elasticsearch’s proven relevance and scalability, we’ve designed a search experience that simply requires you to search the way you'd speak to a colleague, rapidly getting you to the document or answer you need. No need to configure any elaborate applications, traverse through complicated interfaces, or learn any strange conventions: Elastic Enterprise Search understands your intention and lets you remain focused on the task at hand.

Say farewell to the anxious days where multiple browser windows held hundreds of open tabs. Search all of your documents, pull requests, issues, tickets, contracts, spreadsheets — whatever it is, wherever they are, you have a single, organized gateway to getting things done.

Elastic Enterprise Search comes stock with cloud application connectors that get you started in just a few minutes. For this first beta release, we’ve focused on the cloud applications that are most commonly used in today’s modern organizations:

- Google Drive: Search over all of your docs, sheets, slides, and stored files.

- GitHub: Ingest all of your issues and pull requests.

- Salesforce: Sync accounts, contacts, leads, and opportunities.

- Dropbox: Index all of your images, static files, and documents.

- Custom Connector Framework: Sync data from any source, like an internal application, analytics engine, private communication channel, or knowledge base.

Enterprise Search provides privacy groups and tunable search relevance so that the right things are found by the right people. Assign each team member to a group: Engineering, Sales, Marketing, Design, Product, Leadership — whatever best fits your organization — and calibrate their sources’ relevance, based on their specific needs. Adjust the significance of GitHub for your Engineering team, Salesforce for your sales team, Dropbox for your design team; whatever fits. With granular access controls and group assignments, you can securely guide what will be found by individuals and groups. And what will not be found.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...