Customer conversations
Do calls, tickets, reviews, and emails keep telling you what customers need, but no one has time to turn those patterns into better service, sales, or training?
Practical AI built on the knowledge inherent in your business
Your data is already valuable.
It just isn't usable yet.
We're the data team you didn't hire. We pull together the information scattered across your tools, files, and team conversations, then turn it into AI systems your people and customers can rely on — for better answers, smoother workflows, and decisions you can trust.
Our Approach
Your best knowledge is probably woven into the business.
Most teams do not need more vague AI talk or disconnected AI products built for the general public. They need a practical way to find what has been said, written, decided, repeated, and learned by your team.
The common problem
The answers are there, but they are scattered across tools, conversations, files, and people. Torchbearers helps turn that raw material into training, standards, workflows, reporting, and AI systems your team can put to work.
Employee know-how
Do your best people know the right way to handle tricky situations, while new hires learn by shadowing, asking around, or guessing from old notes?
Messy operations
Are the real steps for getting work done spread across spreadsheets, inboxes, task boards, documents, and someone's memory?
Sales and follow-up
Are good objections, winning phrases, deal notes, and follow-up details getting captured somewhere, but never becoming a repeatable playbook?
Client coordination
Do ten people work with the same client while notes, history, preferences, promises, and next steps live in different places?
Meetings and decisions
Do useful context, decisions, and next steps disappear into meeting notes no one revisits when the work starts moving?
Standards and compliance
Do people follow slightly different versions of the same process because the official policy and the real-world workflow are not in sync?
If your team keeps saying, "we know this somewhere," we help turn that somewhere into an AI system trained on your business.
The process
Four layers. Built around how your business works.
We begin by understanding the people, processes, and knowledge your business runs on. Then we build the technical layers that make that knowledge usable.
We start by asking the right questions and learning the business as a whole: what you need, how work gets done, where knowledge lives now, and what your people know from day-to-day experience but have not had a good way to organize.
Connect the systems, documents, notes, and records your tools and AI need to work from — with the right permissions and security in place so people only see what they should.
Define what your terms, rules, and workflows mean inside your business. This turns scattered data into a shared language your team — and the AI — can trust.
Build the tools your team and customers use in practice — chat assistants, automations, internal apps — grounded in your real business context, with guardrails that keep them accurate and safe.
Why us
Built by engineers who've done it in production.
We do the whole chain.
Most boutique data shops stop at dashboards. We go further: connecting your information, teaching the system your business, and building the AI tools your team and customers use in practice.
Governance from day one.
Row-level security, versioned definitions, prompt boundaries, and audit trails are part of the system from the beginning, because agents need guardrails as much as they need data.
You own it. Forever.
Open standards, your systems, your code, your keys. What we build should become your company's own infrastructure, not a dependency on us. If you want ongoing support, we are happy to provide it — but you own the build and the data.
The team
The team
We're software professionals who've spent the last decade researching hard problems and building production data systems - in retail, workforce analytics, logistics, and cancer research. We started Torchbearers because we kept watching companies underuse what was right in front of them: the data, context, and hard-won knowledge inside their own business. Our work is to carry that forward - to help teams turn their own information into something insightful, robust, and actionable.
Jesse Ivers, PhD
AI/ML, Semantic Layers, Software ArchitecturePhD in biomedical engineering from the University of Arkansas, where he used machine learning to better understand cancer - training patented ML/DL systems that interpreted optical microscopy data to characterize treatment response and cellular metabolism. Drove MLOps forward while delivering fully productionized ML models at the largest retailer in the world. Now leading the charge at a rapid-growth company as they build out their first AI platforms and products.
Jesse Keyton, PhD
Machine learning & analyticsPhD in mathematics from the University of Arkansas. Spent three years building analytical tools and predictive models for pricing freight spot quotes at a publicly traded logistics company, directly supporting yield and operations leadership. Now an ML engineer at the same company, owning the full lifecycle of AI/ML applications from problem scoping through production and maintenance.
Steven Homem M.S.
Software Architecture, Agentic Systems, Semantic LayersSoftware engineer at Lightcast building ETL and semantic infrastructure for workforce data. Formally trained in mathematics; previously security and platform engineering at Walmart Global Tech. Currently building multi-agent systems on AWS AgentCore that query semantic layers in production.
Stop paying for generic tools that do not know your business.
Most subscriptions will never understand your workflows, data, clients, or team knowledge. Take twenty minutes on a call and we will help you spot what is scattered, what could be connected, and where a custom agentic platform would make day-to-day work easier.
Book a call