Bridging partners in pursuit of agentic AI — Part 1: Why partnerships matter for enterprise intelligence

October 20, 2025

The pace of change in AI development has been dizzying. In just a few years, we’ve moved from experimenting with AI, machine learning (ML), retrieval augmented generation (RAG), and agents to asking how these innovations can solve real business problems. Enterprises are no longer impressed by the novelty and possibilities; instead, they expect outcomes. AI investments require proof of value, which can be demonstrated by either saving money, generating revenue, or uncovering insights that create a competitive edge.

As the early wave of AI for creativity normalizes, a new frontier is emerging: AI for enterprise intelligence. At the center of this shift is semantic search — the connective tissue that allows organizations to retrieve, interpret, and apply information with context and precision.

From IoT to AI: Following the data to enterprise intelligence

Like many technologists, my path to AI started with data. During the rise of the Internet of Things (IoT), I was fascinated by the ability to collect information that could be used to predict machine failure, pinpoint material breakdowns, and enable smarter operations. The challenge was never about getting data; it was about what to do with it, where to store it, and how to make sense of it.

The breakthrough came when AI matured enough to not only crunch numbers but also to reason. Search, particularly vector search, became the missing link. Instead of relying on keyword matches, it enables systems to understand meaning, context, location, and intention and then follow up.

Joining Elastic allowed me to see this evolution firsthand. Elasticsearch’s vector database has transformed the way we unlock value from data — from powering research platforms like Consensus to enabling enterprises to analyze questions with depth and accuracy.

woman on computer reading AI-generated response

The foundation: Where data meets AI

The foundation for meaningful AI solutions is accurate data and the ability to retrieve it with meaning and context. Elastic is uniquely positioned here.

With the Elasticsearch vector database, enterprises can create, store, and search embeddings at scale. The Elasticsearch Platform supports multiple retrieval methods, including text, sparse, dense vector, and hybrid search, providing developers with the flexibility to pair the right approach with the right AI model. Through the Elasticsearch Open Inference API, teams can seamlessly connect to providers like OpenAI, Anthropic, and others.

The enterprise AI hierarchy: 5 steps to agentic AI

Building AI solutions is not unlike Maslow’s hierarchy of needs: You cannot reach the “self-actualization” of agentic AI without a solid foundation. Each layer builds on the one below it:

1. Foundation: Proven technology
Every journey starts with a solid base. With more than 5B downloads, adoption by 54% of enterprises, and consistent recognition from Gartner, Forrester, and IDC, Elastic is the most trusted and most downloaded vector database. That matters when choosing a platform to power business-critical AI. This foundation ensures that private enterprise data is not just stored but activated and ready to fuel AI securely and effectively.

2. Alignment: Integrations that fit
The next step is alignment. Which providers, ISVs, and cloud platforms do you rely on today and which do you want to add tomorrow? Elastic’s extensive AI ecosystem of integrations and connectors keeps your options open, so you can build with what works best for your enterprise.

3. Partnership: Multiplying value
Technology alignment is powerful, but partnerships make it transformational. By collaborating with Elastic and our partners, organizations move beyond solving immediate needs to scaling solutions that create new value.

4. Execution: Delivering competitive impact
With the proper foundation, alignment, and partners, enterprises can execute confidently. This is where strategy turns into delivery, driving the competitive differentiation you set out to achieve.

5. Outcomes: Agentic AI at scale
At the top of the hierarchy, agentic AI delivers tangible results: improved operations, enhanced customer experiences, and the freedom to innovate. This is where enterprises don’t just meet expectations; they also set new ones.

A lesson from a cork

When I was 11, visiting family on the island of Faial in the Azores, I learned an unforgettable lesson about hidden value. A group of us set out in a small dinghy far from shore and surrounded by Portuguese man o’ war jellyfish. Suddenly, I heard a pop!

The cork at the bottom of the boat — normally used to drain water while on land — had come loose. Ocean water poured in. Instinctively, I plugged the hole with my finger until my cousin found the cork and sealed it back in place. That simple, overlooked piece of material was the difference between safety and disaster.

The partner ecosystem operates in the same manner. Every participant, no matter how small they might seem, plays a role in keeping the solution afloat. Without one piece, the risk of failure rises dramatically. With the correct alignment and collaboration, the system stays strong and delivers value.

Building the AI stack: From foundation to impact

Once the foundation is strong, additional layers are built to form the enterprise AI stack. The Elasticsearch vector database is centrally positioned to bring everyone together, inspiring the Elastic AI Ecosystem:

Infrastructure: Cloud or data center of choice for scalability and compliance
Data prep and ingestion: Ensuring information is accessible, structured, and clean
Search and vector database (Elastic): Unlocking contextual, meaningful retrieval at enterprise scale
AI models and frameworks: From foundation models from OpenAI and Anthropic to orchestration tools from LangChain and LlamaIndex
AI security and operations: Safeguarding data, monitoring performance, and ensuring trust
Applications and Agent Builder: The business-facing layer where solutions become tangible — powering enterprise intelligence, customer experience, and innovation

Elastic’s open ecosystem means these layers don’t live in isolation. Instead, they interconnect with Elastic often serving as the mediator that bridges technologies into a cohesive whole.

The power of ecosystems

When multiple partners align — a search platform, a hyperscaler, a SaaS provider, and an SI — the result is a multipronged collaboration. This is where ecosystems create exponential value, delivering solutions that are not only technically sound but also enterprise-ready, scalable, and impactful.

For enterprise solutions to succeed beyond proof of concept and scale, enterprises need holistic technical integration from start to finish. Choosing the right technology and ecosystem partners to deliver these solutions can mean the difference between progress and failure.

Technical alignment ensures that products and platforms can be effectively connected. Partnership takes it further by ensuring they create value together. When evaluating partnerships, I look at four dimensions:

Business alignment: Do we have an industry-focused story to tell together?
Better together messaging: How do our technologies complement each other to deliver business outcomes?
Target audience: Do we share mutual customers, or can we expand into new markets together?
Resources: Do we have the people, funding, and commitment to execute?

Elastic approaches partnerships with this lens. Our recognition as Partner of the Year with Microsoft, Google, and AWS is not just about technical integrations. It reflects the depth of collaboration and shared execution, and that strength extends to the rest of our ecosystem.

A customer example: Ernst & Young

Elastic has been applying generative AI (GenAI) solutions since its onset. Ernst & Young (EY) developed a GenAI solution that integrates Elastic with LlamaIndex, LangChain, and LanceDB, resulting in actionable insights for compliance and finance innovation. Elastic’s role wasn’t just about search; it was about seamless integration across multiple partners that accelerated development while ensuring enterprise-grade performance.

Looking ahead: From experiments to impact

Building AI agents is complex. Building agentic AI solutions — systems that adapt, scale, and drive measurable results — is even more challenging. Enterprises need confidence that integrations are already in place, that ecosystems work together, and that the path forward is clear.

That’s where Elastic and its AI Ecosystem help simplify the journey. By connecting the right technology providers and partners and lowering the barriers to integration, we help enterprises transition from experimentation to impact more quickly.

Enterprise leaders are done with AI experiments. They’re ready for scalable solutions that integrate seamlessly, deliver measurable value, and stand the test of time. With Elastic’s AI Ecosystem and the right partner collaboration, that future is within reach.

If you’re seeking to elevate customer experiences with GenAI-powered applications, Elasticsearch provides the open and comprehensive set of capabilities developers need to build enterprise-grade, production-ready solutions faster.

Explore our extensive integrations, Elastic AI Ecosystem, and Partner Directory to see how we integrate and innovate together.

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