The conversation around artificial intelligence has shifted. Not long ago, AI was judged mainly by its brilliance. Could it solve advanced problems? Could it reason creatively? Could it understand the nuances?
Today, enterprise leaders are asking a very different question. Can it be trusted?
This new priority has revealed a surprising challenge. Even the most advanced AI systems can excel at complicated tasks but still make baffling mistakes on simple ones. A model may navigate a complex workflow yet struggle when a customer mumbles a question on a noisy phone call. This is what researchers refer to as jagged intelligence, and it is one of the biggest barriers to deploying AI agents safely at scale.
Salesforce’s new simulation environment called eVerse was created to confront this challenge head on. It is not another tool layered on top of existing systems. It is a foundational shift in how AI agents learn, improve, and ultimately perform in real enterprise scenarios.
What Is eVerse and Why Does It Matter
eVerse is an enterprise simulation platform that allows AI agents to train in highly realistic and completely synthetic environments. These environments mirror the complexity of real-world interactions without exposing any sensitive customer or operational data.
In simple terms, eVerse gives AI the training experience it always needs.
Agents interact with lifelike voice conversations, unpredictable human personas, and multilayered workflows that resemble what truly happens inside a business.
This matters because enterprise operations are rarely clean or predictable. Customers call from busy streets. Speakers overlap. Connections cut in and out. People explain their problems out of order or with emotion. Traditional AI training does not prepare agents for these messy realities. eVerse does.
The Three Step Engine Behind eVerse
At the heart of eVerse is a continuous learning cycle built around three key stages.
Synthesize
The platform generates fully synthetic training grounds. These environments recreate customer data patterns, workflow structures, and rare edge cases that are difficult to observe in real life. They also simulate complex voice conditions such as thick accents, background noise, and overlapping speakers.
Measure
Agents are tested across thousands of scenarios. Performance is evaluated by an automated judging system that identifies exactly where the agent succeeds or fails. It highlights specific issues such as inaccurate intent recognition, incorrect action sequencing, or slow response times.
Train
After weaknesses are identified, agents undergo targeted training with reinforcement of learning shaped by human feedback. The improvement is significant and measurable. Early research shows that agents trained through eVerse can jump from nineteen percent to eighty eight percent success across enterprise tasks.
Real Impact in Real Industries
The most powerful proof of eVerse comes from early pilots.
Healthcare Billing with UCSF Health
Billing in healthcare is notoriously complex because so much knowledge is undocumented or situation specific. By training through eVerse, AI agents at UCSF Health were able to handle both routine and nuanced inquiries with far greater accuracy. The result was a smoother and more patient-friendly billing experience.
Agentforce Voice
Before Salesforce launched its new voice capabilities, the system underwent thousands of simulated conversations in eVerse. These conversations included broken audio, difficult accents, crosstalk, and emotionally charged callers. This preparation allowed Agentforce Voice to perform reliably when placed in front of real customers.
These examples show what becomes possible when AI is trained with the same rigor used to prepare pilots, athletes, and emergency responders.
The Rise of Enterprise General Intelligence
Most conversations about AI focus on general intelligence. Yet enterprises need something more practical: dependable intelligence. This is where the concept of Enterprise General Intelligence comes into play.
Enterprise General Intelligence is not about creating a model that can do everything. It is about building AI agents that consistently perform well across the specific and high stakes workflows that keep businesses running.
eVerse pushes AI toward this level of reliability through controlled, repeatable, and realistic practice environments. It transforms agents from clever pattern matchers into trustworthy digital teammates.
Why Simulation Will Define the Next Era of Enterprise AI
Going forward, the organizations that succeed with AI will not simply be the ones with the biggest models. They will be the ones that prepare their agents in environments that mirror the real world with precision.
Simulation is emerging as the new infrastructure layer for enterprise AI. It allows teams to train agents at scale, test them safely, and refine them continuously. Over time, this will produce AI that behaves with the confidence and steadiness that enterprises demand.
The launch of eVerse marks an important moment. It signals a shift away from curiosity and experimentation toward a future where AI is dependable, measurable, and ready for mission critical use.
We are entering the Reliability Era of AI, and eVerse is one of the platforms leading the way.
Take the Next Step Toward Reliable AI
If your organization is preparing to introduce AI agents or scale automation across customer service, sales, billing, or operations, this is the right moment to reimagine how those agents are trained. Simulation is rapidly emerging as the foundation for enterprise level reliability, giving teams the confidence to deploy AI in mission critical environments.
Connect with the Saksoft AI expert team to explore how eVerse can accelerate your transformation and strengthen the performance of your AI initiatives. The organizations that embrace reliable and simulation driven training today will be the ones shaping the next generation of AI empowered enterprise success.
Nilamani Das
Nilamani is a thought leader who champions the integration of AI, Data, CRM and Trust to craft impactful marketing strategies. He carries 25+ years of expertise in the technology industry with expertise in Go-to-Market Strategy, Marketing, Digital Transformation, Vision Development and Business Innovation.
