Going beyond generic AI: How Trovia keeps institutional knowledge alive

One of the defining strengths of mid-size companies is their deep institutional knowledge. This includes years of best practices, rich company history, and business-related nuance, all of which separates the organization from its competitors. So, when these businesses use generic AI systems built exclusively on internet-trained data, they risk losing what makes them unique.

Together with Amazon Web Services (AWS), AI startup Trovia is ensuring that mid-size companies can use AI to scale their expertise intelligently and securely. Using services like AWS Lambda, Amazon Bedrock, and AWS Fargate, Trovia consolidates institutional knowledge into a single source of truth, improving the AI tools companies are already using. With no coding required, Trovia is simple to use, allowing businesses to easily extract best practices from their top people, so their knowledge base stays up to date and grows in accuracy over time.

AI’s context crisis

Following years of experience building enterprise-grade AI systems firsthand, Trovia’s founders identified a key challenge for any business looking to operationalize AI: “We found that in order for agentic systems to work well, we needed to feed them contextual content. But there were hundreds, even thousands, of such documents that covered a plethora of topics and in many different formats,” explains Aaron Rallo, CEO and co-founder of Trovia.

When this content was put in front of AI agents, they would interpret it literally, or misinterpret it entirely, before synthesizing the content into a believable, but most likely incorrect, answer. Rallo adds, “We ended up having to use hundreds of hours of human time to fill these gaps and get answers that we were confident in. It was a lot of work and not a durable solution. This problem stuck with us as something that needed to be automated and would benefit any company looking to use AI systems, and especially those that don’t employ engineers.”

The alternative to companies using their own content is to rely solely on the generic models trained on the internet. This presents a different problem. For mid-market organizations that are built on deep institutional knowledge, generic AI solutions can limit competitiveness. Rallo explains, “If you have an AI system for your business that’s trained on the same data as your competitors, you’re going to start looking more alike over time. Your systems could become really generic, really fast, and you could lose your differentiation.”

These challenges sparked the inspiration for Trovia. Trovia’s founders created a solution that consolidates, validates, and pressure tests content before it is used by AI systems. “We created a system that could go through all the content up front, anticipate the questions a person might ask and then confidence score those answers,” explains Rallo. “Then, we packaged it all up and made it accessible so that anybody could use it, including the mid-markets and folks that don’t have their own AI engineers”.

From documentation to differentiation

“What Trovia is really good at is extracting information from knowledge repositories, including operational policies, procedures, and documentation on maintaining equipment or handling customer service incidents,” says Rallo. By adding both business documentation and institutional knowledge to Trovia over time, customers create a knowledge layer, so their AI tools provide relevant, specific, and accurate answers instead of generic or synthesized ones. “Trovia will never synthesize an answer. If a question comes up that it doesn’t know the answer to, it will direct to a human for an answer. Once captured, the knowledge layer is updated,” adds Rallo.

Scaling smarter

From the outset, the Trovia team built their product on AWS, leveraging its flexibility, scalability, and global reach. Rallo explains, “The reason we built on AWS is we knew this was going to get really big, really fast, and we needed secure, scalable architecture from the start.” Trovia’s co-founder and CTO Gabriel Wiebe adds, “Our capabilities are not only growing horizontally but also geographically, so we also needed multi-region support and geo-segmented data strategies.”

Trovia was built using multiple AWS services, including AWS Lambda for serverless infrastructure management and AWS Fargate for simplified container management. Wiebe explains, “If I need a service, I know AWS has it in its portfolio.” Rallo adds, “This is hugely valuable and it allowed us to build much faster. In fact, Trovia went from an idea to a working product in just three months.” The Trovia team also used multiple AI services through Amazon Bedrock. “Having access to different models through Amazon Bedrock has been great. We primarily use Anthropic, including Claude Code for coding assistance, but we also use Amazon Nova and OpenAI, and this has made our development easier and faster,” says Rallo.

Trovia in action 

A lighthouse customer for Trovia is Synergy Franchising, a multi-unit franchise operator managing a growing portfolio of 38 Popeye’s and Firehouse Subs quick-service restaurants. Before implementing Trovia, whenever team members had pressing questions about anything from faulty equipment to company policies, they would contact Synergy leadership by email, text, or WhatsApp. Not only was this process time consuming for the Synergy team, but it also yielded inconsistent answers that changed based on the respondent.

With Trovia, all of Synergy’s institutional knowledge is consolidated and validated into a single source of truth. Using Trovia’s platform has already saved time handling requests since employees can now get consistent and accurate answers to their questions. Now, Synergy is targeting a 75 percent reduction in tickets, calls, and emails.

Synergy also aims to reduce the number of unnecessary support call-outs of technician personnel by 20 percent. Using Trovia, the onsite team can access the knowledge layer to resolve issues on their own or diagnose problems before a technician is deployed.

Kyle Ferbey, Chief Operating Officer at Synergy, says, “With Trovia in place, we can do diagnostics earlier on in the process. For example, before we send a technician to troubleshoot an issue with an appliance, we can have a team member take a picture of an error code or piece of equipment, send it to Trovia, and troubleshoot the problem before a human has to be engaged.”

Synergy is targeting a 75 percent reduction in one-off messages and phone calls from their 650 employees to their senior staff. Synergy’s favorite feature is Trovia’s ability to integrate with its existing systems. “Today, we use email, WhatsApp, and text, and Trovia now sits in line with all those things. We didn’t have to introduce anything new” adds Ferbey. Today, Trovia is helping Synergy’s 650+ employees deliver a more consistent and efficient hospitality experience.

Accelerating the knowledge engine

As Trovia continues to scale its reach and its capabilities, the startup will expand its use of AWS services. With Trovia’s customers being rightfully cautious about feeding their institutional data into AI systems, data sovereignty will play an increasingly important role. Gabriel Wiebe, CTO and co-founder at Trovia, explains, “Having all the capabilities, access controls, encryption layers, and data segmentation that AWS provides is really important to our customers. I know AWS can deliver as we grow our services and our capabilities across larger domains.”

With the startup still building out its portfolio of offerings, Trovia is also looking to take advantage of Amazon Bedrock AgentCore’s plug-in architecture and build-in guardrail support. “We’re going to have to meet the customer where they are, and Amazon Bedrock AgentCore is going to help us deliver tailored integrations for every customer much faster,” says Wiebe. Trovia is also in the process of joining AWS Marketplace to make it simpler for customers around the world to find and onboard the startup’s technology.

Today, Trovia is excited to expand within the franchising and property management verticals. Rallo says, “Human knowledge is extremely valuable today, and it’s only going to grow in value as we continue to implement AI. Systems like Trovia that can learn continuously help to make sure that this knowledge is amplified, not replaced.”

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