OpenEvidence AI: What it is & what it means for support teams in 2025

Kenneth Pangan

Stanley Nicholas
Last edited November 6, 2025
Expert Verified

It feels like a new AI tool pops up every single day, right? But every now and then, one comes along that really makes you sit up and take notice. For me, that’s OpenEvidence AI. It’s a tool built for doctors, but its wild success is a masterclass in how to build AI that people actually trust and use in a high-stakes job.
So, what exactly is OpenEvidence AI, and why should a customer support leader care?
In this post, we'll look at what makes this platform tick. But more importantly, we’ll dig into the lessons its success holds for anyone trying to bring smart AI into their customer or internal support. The principles that made it a go-to for doctors are the very same ones that can seriously level up your support operations.
What is OpenEvidence AI?
At its heart, OpenEvidence is an AI assistant designed to help healthcare professionals make better clinical decisions. It lets verified clinicians ask complicated medical questions in plain English and get back accurate, evidence-backed answers almost instantly. Think of it as having a brilliant medical consultant on call 24/7.
The platform’s real magic isn’t just its AI model, but where it gets its information. Every answer comes from trusted, peer-reviewed medical sources like The New England Journal of Medicine (NEJM), JAMA, and the NCCN Guidelines®. This focus on reliable sources means doctors can feel confident using the information when making important decisions about patient care.
To keep the quality high, OpenEvidence is only available to verified healthcare professionals who have a National Provider Identifier (NPI) number. This gatekeeping has clearly worked. According to investors like GV (Google Ventures), over 40% of U.S. physicians are now using the platform. That kind of growth, driven by a "Direct to Clinician" approach, shows that when you give professionals a tool that’s both powerful and easy to use, they’ll actually use it. A lot.
Key lessons from OpenEvidence AI's success for support teams
Okay, so OpenEvidence AI has clearly figured out its niche. But the reasons it works so well are universal and have everything to do with the world of customer support. The platform gives us a blueprint for moving away from clunky, generic chatbots and toward genuinely intelligent AI assistants.
Lesson 1: Generic AI isn't enough, context is king
The secret sauce for OpenEvidence AI is its highly curated, domain-specific knowledge. It gives reliable answers because it's trained on expert medical literature, not the entire, chaotic internet. It gets the nuances of medicine because its entire world is medicine.
This is a painful lesson many support teams have already learned. Generic AI assistants often fall flat because they have zero business context. They don’t know your specific return policy, the five steps to troubleshoot your main product, or the friendly brand voice you’ve spent years building. This just leads to frustrated customers and more work for your human agents who have to jump in and fix the mess.
This is exactly why a specialized platform like eesel AI is so much more effective for support teams. It’s built to learn from your company’s unique knowledge. It doesn't just know about customer support in general; it knows how your team handles support. By connecting directly to your past support tickets, internal wikis in Confluence, and docs in Google Docs, it can provide answers with the same kind of contextual accuracy that doctors get from OpenEvidence.
This infographic for OpenEvidence AI shows how eesel AI centralizes knowledge from different sources to power support automation.
Lesson 2: Trust is built on evidence and accuracy
In medicine, you can't mess around with trust. A wrong answer can have serious consequences. OpenEvidence AI builds confidence by citing its sources for every single answer, letting doctors quickly check the information and see the evidence for themselves.
Customer trust is also incredibly fragile. An AI that "hallucinates" a wrong answer or makes up a company policy can destroy a customer relationship in seconds. You can't afford to gamble with a tool that might confidently steer a customer in the wrong direction.
Building that trust is a core part of the eesel AI platform. Before your AI agent even thinks about talking to a customer, you can use its simulation mode to test it on thousands of your own past tickets. You can see exactly how it would have answered real questions from your customers, check its work, and tweak its behavior. This gives you a clear picture of how it will perform and the confidence that it’s a reliable part of your team, not a loose cannon.
The eesel AI simulation feature provides a safe environment to test the OpenEvidence AI.
Lesson 3: Seamless integration drives adoption
Part of what made OpenEvidence AI take off is how easy it was for doctors to start using it. It's a free, simple app that fits right into their workflow. There was no need for a long sales process or getting the whole hospital to sign off on it; doctors could just download it and get going.
This is a huge contrast to the headaches many support teams face with new tools. Too many platforms require you to ditch your existing helpdesk, spend months on a complicated setup, or force your team to learn a whole new way of working. All that friction is a massive barrier, and you might not see any real benefit for months.
eesel AI is built on that same idea of easy integration. It offers one-click connections to the helpdesks your team already uses every day, like Zendesk, Freshdesk, and Intercom. Instead of making you change your tools, eesel AI works with them. You can be up and running in minutes, not months, and start seeing results right away.
How to build your own OpenEvidence AI for customer support
The success of OpenEvidence AI isn't just a cool story; it's a practical guide. By following these same principles, you can build a powerful, context-aware AI for your own support team. Here’s how you can get started.
Unify your scattered knowledge sources
Let's be honest: for most companies, the "knowledge base" is a bit of a disaster. Information is spread out everywhere, help center articles, internal engineering wikis, random Google Docs, important Slack threads, and all the wisdom locked away in years of old support tickets.
The first step toward a brilliant AI is to pull all those scattered sources into one brain. With eesel AI, this isn't some manual, multi-month data project. You can connect to over 100 sources with just a few clicks. For example, you can train your AI on your official Zendesk help center, your internal product docs in Confluence, and your team's best-practice guides in Google Docs. This creates a single source of truth from day one, giving your AI the context it needs to be genuinely helpful.
Define clear rules and custom actions
A great support AI needs to do more than just find answers. It needs to be an active part of your workflow. It should be able to do things like escalate a ticket to a senior agent, look up a customer's order, or tag an issue for the product team.
To make that happen, you need to be in the driver's seat. The eesel AI prompt editor lets you define your AI’s exact persona, tone of voice, and rules for escalation. You can tell it when to answer, when to loop in a human, and how to talk to customers.
Even better, you can create custom actions that let your AI interact with your other tools. It can check live order information from Shopify, create a new bug report in Jira, or correctly tag and route a ticket in Freshdesk, all on its own. This turns your AI from a simple Q&A bot into a true automated agent.
A screenshot of the customization and action workflow screen in eesel AI, relevant for the OpenEvidence AI blog.
Test, simulate, and roll out with confidence
Launching a new customer-facing AI can be nerve-wracking. How can you be sure it's ready? How do you know what impact it will have before you flip the switch?
This is where a solid simulation tool is a lifesaver. Before going live, eesel AI lets you run your new agent against thousands of your historical support tickets in a safe environment. The dashboard then gives you a clear report showing which tickets it would have solved, what its answers would have been, and your estimated automation rate and cost savings. This data-first approach lets you make smart decisions, fine-tune the AI, and roll it out gradually with total confidence.
OpenEvidence AI pricing vs. a support AI platform
A big reason for OpenEvidence AI's explosive growth is its price: it's free for verified U.S. healthcare professionals. This was a smart move that removed any barrier for individual doctors to give it a try.
While that's great for their market, AI platforms for business usually follow a more standard subscription model. In the support world, the trick is to find a provider with clear, predictable pricing that doesn't punish you for doing well. A lot of AI tools charge you per resolution, meaning your bill goes up as the AI gets better at its job.
eesel AI offers a straightforward pricing structure based on a set number of monthly AI interactions. There are no surprise fees per resolution, so your costs are predictable, even when you’re having a busy month.
| Plan | Monthly (bill monthly) | Effective /mo Annual | AI Interactions/mo | Key Features |
|---|---|---|---|---|
| Team | $299 | $239 | Up to 1,000 | Copilot for help desk, Slack/Teams chat, train on public docs. |
| Business | $799 | $639 | Up to 3,000 | Everything in Team + train on past tickets, custom AI Actions, bulk simulation. |
| Custom | Contact Sales | Custom | Unlimited | Advanced security, custom integrations, multi-agent orchestration. |
This video explains why doctors consider OpenEvidence AI a game-changing tool in the medical field.
The future is specialized AI
OpenEvidence AI proves a simple but powerful point: the future of useful AI is specialized. Generic, one-size-fits-all tools just don't cut it anymore. Just like modern medicine needs an AI with deep clinical knowledge, world-class customer support needs an AI that deeply understands your business, your products, and your customers.
Your team deserves its own "OpenEvidence", an AI that’s accurate, trustworthy, and fits right into the tools you already use every day. An AI that doesn't just answer questions, but actually solves problems.
Ready to build an AI that's as smart about your business as OpenEvidence is about medicine? Start your free trial of eesel AI and deploy a context-aware AI agent in minutes.
Frequently asked questions
OpenEvidence AI is an AI assistant designed to help healthcare professionals make better clinical decisions by providing accurate, evidence-backed answers to complex medical questions. It acts like a brilliant medical consultant available instantly, helping doctors access crucial information quickly.
OpenEvidence AI is exclusively available to verified healthcare professionals who possess a National Provider Identifier (NPI) number. This gatekeeping measure ensures that only qualified medical practitioners can access and utilize the platform's specialized knowledge.
OpenEvidence AI ensures accuracy by sourcing all its answers from trusted, peer-reviewed medical literature, such as The New England Journal of Medicine and JAMA. This focus on reliable, expert-vetted sources allows doctors to feel confident in the information provided.
Its success stems from a combination of highly specialized, context-aware AI, a strong emphasis on trust through cited sources, and seamless, free access for verified clinicians. This "Direct to Clinician" approach, coupled with its ease of integration into workflows, made it highly adoptable.
Yes, OpenEvidence AI is currently free for verified U.S. healthcare professionals. This strategic pricing model removes financial barriers, encouraging individual doctors to quickly adopt and integrate the tool into their daily practice.
Customer support leaders can learn that specialized, context-aware AI, built on trusted, internal knowledge, is far more effective than generic AI. Creating an AI that deeply understands your specific business and integrates seamlessly into existing workflows builds trust and drives adoption.




