StitchStudio’s insurance-specific
ontology and configurability to organization-
specific knowledge is their secret sauce for improving operations
By Lori Widmer
The process of automating an agency or brokerage is often stymied by not knowing where to start. Heavy workloads exist along much of the pipeline, which can create backlogs, introduce errors, and lead to customer dissatisfaction.
With decades of experience in the industry, Karan Mishra, CEO of StitchStudio, and founder Santoash Rajaram looked for a way to “meet the market where the market is,” as Mishra puts it. That meant creating a way to deliver exactly what each agency needs to transform and empower its workflows.
StitchStudio’s ethos is to make AI accessible to organizations. Moreover, the company set out to ensure that the automation of workflows was tailored to the specific function or functions of the client organization.
Drawing upon Mishra’s 20 years of experience within insurance consulting, working with carriers and brokers, he and Rajaram determined that automation was a huge market demand, but that many vendors were falling short of delivering what agencies needed—scalable AI.
“The industry is very nuanced,” says Mishra. “There is a lot of regulatory burden that sits with the insurers. When you are looking to optimize workflows, improve expense ratios, basically touch anything on the core operation side of an insurance company or a broker, it’s really important for that product to deliver to the market a solution that’s trust-based.”
StitchStudio’s AI solution “manages the complexity of the regulated environment, manages compliance against that complexity, and thinks of the product itself as an enablement for the humans.”
StitchStudio was built to deliver on three core principles: to be explainable (from a compliance/regulatory perspective), to be auditable, and to be predictable. The product also has to respond to the technicality and variety of situations within the insurance industry. “What we built was something that meets the uniqueness of this industry at a line-of-business-specific level, which helps (clients) resolve the complexity of a regulated, compliant, and necessary environment,” says Mishra.
[The company] create[s] a way to deliver exactly
what each agency needs to transform and empower its workflows.
To build the right AI solution, Mishra says, requires the right product company with the right focus. He says that starts with a team that “understands the nuances of each of the lines” of business. Another important element, he says, is that technology itself delivers the solution’s three core principles.
Finally, Mishra says, the product company should be partnering with clients to design a solution that works for them, but also for the market and industry as a whole. “You need to think of every single organization’s operational workflow that you are automating as a last mile. You should solve for the 80% of the box. But just as important is the ease of solving that last 20% and to solve it effectively.”
What users say
For Kate Grasman, that “solve” gained her company a 50% increase in efficiency in initial testing. Grasman, chief information officer for Heffernan Insurance Brokers, says she and her team were looking for something that was efficient and made work easier for the producers.
Heffernan had a carrier database that wasn’t being updated regularly. “It was a manual process that was very labor intensive,” says Daniel Grasman, high school intern for the company who was assisted by two other high school interns. Daniel was part of the pilot intern program two years ago for the company. (Feedback from that pilot has allowed Kate’s team to grow and improve the program.) Information was being passed from employee to employee through emails and, according to Daniel, was “based off their knowledge” of a carrier’s particular appetite for risk.
To find the best solution, Daniel researched eight vendors. He led the conversations with vendors, including product demos and asking how each product was going to help Heffernan. “I just found that working with the StitchStudio people, they had specific solutions for Heffernan that I wasn’t really getting” elsewhere. He presented his findings and recommended StitchStudio’s AI solution to the Heffernan executive team.
What Heffernan bought: StitchStudio’s AI solution scans emails and delivers more accurate, current reports on carrier appetite. Why StitchStudio works, says Kate, is that “it was more agentic, meaning it had workflows where you have a human in the loop working through these different workflows. We like it because it wasn’t their model that they’re pushing out. They have 15 different lines of business one can choose.”
Another bonus for Kate: “I didn’t have to do all the research or develop. They did a little bit. They had their workflows, and they did a little bit of development for Heffernan, which is a great model for development, to make it fit for the purpose of our business users.
“They built the models using all the available AI tools, and they are delivering the underlying technology to do all the things we’re asking them to do. It is really a wonderful way to work with Agentic AI where we get the best of what they built and it is slightly customized to our specific needs.”
For Kate, the solution solves a sore spot she’s been dealing with since joining the company nearly four years ago. She looked at various technologies to build a niche solution internally, but StitchStudio, she says, had a solution that fit right now.
“You’re going to get that while looking at different AI companies; you’re going to find solutions that are great, but you don’t need right now,” says Daniel.
Onboarding was easy. “Working with Santoash, I just believed in him and the way he got our business problem; the way he worked with our intern team, I knew they were the right partner to work with,” says Daniel.
Final implementation of this phase with StitchStudio was February 13, 2026, but even before the solution was fully implemented, Kate found that people using the carrier database were getting a 50% boost in finding and connecting with carriers. “We were in a 50% increase in matching and placing insurance with the carriers that would accept it based on our initial trials. More to come once we deploy the solution and watch it grow over this next year.”
Smarter use of AI
Mishra says that AI can be used effectively to transform an organization’s efficiency. “I think of it as the product set out to solve the fingerprint problem for our industry, where every organization is very specifically nuanced using AI,” he says. “We have gone about solving for that, and with a trust-based, insurance-specific lens that delivers ROI and speed to market,” a promise that most products have struggled to deliver, he adds.
“AI is a reality that’s here to stay,” says Mishra. “Anybody who’s thinking about AI should start using AI. If AI seems too scary, pick up the phone and call us, because it shouldn’t be.”
For more information:
StitchStudio
Stitch.ai
The author
Lori Widmer is a Philadelphia-based writer and editor who specializes in insurance and risk management.
