Foundations, models, and the intelligence to run them.
Telemyr is an applied AI consultancy founded by an AI research scientist and a CTO/COO who scaled an LVMH-backed business from the inside. We do not sell tools or rent intelligence. We build the data infrastructure, machine learning, and automation that businesses can own outright, deploy across the full P&L, and operate without us in the room.
OUR STORY
Why Telemyr exists
We started this company because we kept seeing the same pattern. Companies feeling urgent pressure to "do something with AI", buying their way into a sea of half-good solutions, and ending up with a stack of overlapping platforms that each gave a different answer and none of which they owned. Marketing had its tool. Finance had a different one. Operations had a third. Nobody trusted the others' output. The experiments multiplied. The results did not. Speed without structure just gets you lost faster.
The companies getting real value from AI are not buying more tools. They are building the foundation underneath them. That is the work Telemyr exists to do. We help businesses own their intelligence and own their data, so they can use the latest LLM and machine learning capabilities at a fraction of the cost, with results that compound rather than reset every time a vendor's pricing changes. Our goal is simple: make the path to real AI clear, build the infrastructure that makes it work, and leave the business operating it independently when we are done.
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Inventory reduction achieved while continuing to grow the business Across engagements, working capital freed by replacing manual planning with AI-driven decision intelligence.
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Operational scale delivered in our founders' last business Before exit to LVMH as strategic partner. The methodology behind Telemyr is built on real scaling experience, not theory.
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Reduction in outbound shipping cost on a single engagement Driven by AI-powered cost modelling, structured RFQs, and supplier benchmarking grounded in invoice-level data.
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DTC conversion rate improvement Achieved by giving customers the right delivery options in the right markets, made possible by the underlying data infrastructure.
SERVICES
Most AI consultancies start with the technology and try to make it fit. We start with the outcome and work backward. Every engagement is judged against one question: did the business run better afterwards? The answer depends on getting four things right, in the right order: the data foundation, the strategic context encoded into the models, the deployment of AI where it earns its place, and the transfer of capability to the team who will operate it. We do all four, in your cloud, on your accounts, with everything you build remaining yours.
Data Infrastructure
We audit what exists, where it lives, what is accurate, and what is missing. Then we build the foundation. Clean, connected, trusted data is what separates AI that earns its place from AI that hallucinates with confidence.
Machine learning and AI
Predictive models, LLMs, and agents deployed where they add real value. Demand forecasting, cost modelling, conversion analysis, and the patterns humans cannot see at scale. Grounded in your real data. No black boxes.
Automation
The manual work that consumes operational teams every week, replaced by systems that run without intervention. Less coordination, fewer errors, more capacity for the work that actually moves the business forward.
Enablement
Every engagement ends with documentation, training, and handover. The team owns the systems. The data sits with you. The intelligence keeps compounding without us in the room.
QUESTIONS WE GET ASKED
Most of these come up in the first conversation. The short answers are below. The longer ones are better in person.
Want to discuss more?
How do you ensure our data remains secure?
Your data stays in your environment. We build inside your cloud, on your accounts, under your access controls. Nothing is copied to a Telemyr environment, no third-party platforms hold your information, and every system we deploy is yours to audit, modify, or shut down. Where AI models are involved, we use private endpoints and grounded retrieval so prompts and outputs never train external models.
