How Elastic Support uses AI to deliver faster, expert-verified solutions

As a valued Elastic customer, you deserve clarity on where automation ends and expert judgment begins. At Elastic, we provide two distinct paths of support:

• Customer self-service: The Support Assistant is available directly in a Support Portal, enabling you to get immediate, automated answers to many questions without waiting for a human.

• Expert-augmented support: When a case is opened, our support engineers use that same Support Assistant as a powerful companion to help investigate and formulate your solution.

This post focuses on the latter: the "human-in-the-loop" use case. While we use advanced AI and retrieval augmented generation (RAG) tools, such as Support Assistant, to accelerate our ability to deliver credible answers, these tools are not designed to replace human technical resolution. We want to provide a transparent view of how our experts critically review, validate, and refine AI-suggested content. Our goal is to ensure we provide accurate, high-quality, and expert-verified solutions instead of automated responses.

Every solution provided by Elastic Support is built upon a rigorous validation framework led by a human support engineer. Our four-step process is designed to eliminate our customers’ reliance on unverified information by:

1. Checking self-service history

2. Understanding the core ask

3. Verifying knowledge first

4. Reproducing the issue

Let’s dive into each step.

Our due diligence begins before the engineer starts the investigation. We first check if you've already chatted with the Support Assistant. This ensures we stay laser-focused on the real aspect of your issue to avoid duplicative efforts. 

Our interactions always start with a human engineer who ensures they fully grasp the technical context, the impact of the issue, and the desired outcome. We prioritize asking clarifying questions to accurately define the problem scope.

Before any AI suggestions are considered, our engineers consult our proven knowledge base. This includes similar resolved cases, official product documentation, Elastic expert content, and detailed internal discussions. This ensures our path forward is always grounded in solutions that have been tested and verified by our experts.

Where feasible, the engineer will always attempt to reproduce the issue in a controlled environment. This vital step confirms the root cause, prevents potential side effects, and ensures the suggested solution works reliably in a real-world scenario. AI can autonomously execute predefined reproduction workflows and validate known failure modes, while our support engineers remain responsible for interpreting ambiguous signals, handling novel issues, and confirming root cause.

Our use of AI is centered on the principle of using it as a companion in one or any of these three specific functions:

• Role A: The expert assistant for research

• Role B: The secure environment replicator and test data generator

• Role C: The solution write-up editor

Support Assistant acts as a powerful knowledge synthesizer. It accelerates the internal research process by quickly sifting through vast amounts of data and suggesting potential solution hypotheses.

One of the most complex steps in support is reproducing a customer's specific technical environment. AI-assisted tooling solves this challenge securely by enabling our engineers to recreate representative, realistic test environments without exposing or requiring any sensitive customer data.

The key principle is simple: AI output must replicate the shape of the customer's system, not the customer's data.

Engineers use AI as a secure blueprint generator to produce artifacts for safe experimentation, validation, and hypothesis testing, such as:

• Synthetic test data: Generating sample data that is structurally accurate and based on your system's schema, allowing us to test solutions without needing your data records

• Mock configurations: Transforming complex customer environments into something we can safely run in our labs, mirroring index patterns, templates, and cluster layouts

• Simulated behavior: Helping find subtle errors like the single typo in a complex configuration a human might otherwise overlook, enabling faster testing of error conditions

All these artifacts are automatically sanitized because AI creates them from scratch based on structural information, ensuring no user data is copied or reused. This allows our engineers to safely experiment and validate solutions much faster.

Once the engineer has successfully validated and found the correct technical solution, AI is used in the final stage to support solution write-ups. 

The clarity imperative: Elastic has engineers in 27+ countries, speaking 13+ languages, and our customer base is equally diverse. To ensure the expert-verified answer is presented to you with optimal clarity and professionalism, regardless of the native language of the engineer or the customer, we use AI to: 

• Perfect grammar, tone, and readability

• Structure multistep instructions logically

• Ensure code snippets and configurations are formatted cleanly and accurately

The result is a technically sound solution that is also easy for you to implement, reducing confusion and follow-up time.

Our commitment to expert-verified, high-quality support is continuous. We believe that curiosity and learning are essential to meeting our customers' needs. The best way for us to ensure our processes, including the use of  AI/RAG tools and our engineer validation steps, are working effectively is through your candid feedback:

• When using the Support Assistant directly: If the tool provides the answer you need, please hit the 👍 thumbs up button. If it does not meet your expectations, hit the 👎 thumbs down button. We use this feedback internally to continuously train and improve the model — the more we use it, the better it gets.

• During a support case: Please share your thoughts, critiques, or suggestions regarding the clarity and accuracy of a solution directly with the Support Engineer handling your case.

• After case resolution: Respond to the satisfaction survey you receive after your case is closed.

Your feedback is invaluable. It helps us refine our due diligence process and ensures we maintain the high standards of accuracy, transparency, and trust you expect from Elastic Support. We read all of your feedback — the positive and the constructive; it helps direct how we improve the service.

We view AI as a force multiplier for technical talent. Our strategy focuses on accelerated intelligence, using generative tools to handle the heavy lifting of log analysis and documentation retrieval in seconds. This automation acts as a launchpad for our already amazing experts, allowing them to dive straight into high-level problem solving. At Elastic, AI provides the speed, but our human engineers provide the nuanced judgment and accountability that your mission-critical systems demand.

When you engage with Elastic Support, you are engaging with a global team of specialists whose deep knowledge is now amplified by best-in-class AI technology, all while retaining the critical oversight that ensures confidence and accuracy.