Compute fit
You're paying for compute you can't use.
Modern workloads changed shape faster than the systems built to execute them. Todd co-founded TAHO Labs to close that gap: break the work into smaller units, route each one to the resource that fits, and pack hardware that currently runs near empty.
The constraint has moved from capacity to execution.
Execution efficiency
More hardware does not automatically mean more throughput.
Modern environments mix CPUs, GPUs, accelerators, cloud, on-prem, and edge capacity. The value comes from making that capacity usable.Infrastructure layer
The critical layer sits beneath orchestration and above hardware.
TAHO is not a replacement for Kubernetes, SLURM, Ray, vLLM, or existing infrastructure. It focuses on how executable work reaches the resource best able to run it.The old answer was more compute. The new answer is compute fit.
For decades, scale solved the most important computing problems. That answer still matters. It is no longer complete.
- Workloads are larger, more dynamic, and more distributed than the systems originally built to run them.
- Infrastructure teams compensate with more orchestration, placement logic, management layers, and manual coordination.
- Utilization, cost, latency, and operational complexity increasingly become different symptoms of the same mismatch.
- AI infrastructure makes the mismatch harder to ignore because high-value work now spans many resource types and execution environments.
TAHO Labs
TAHO changes the unit of execution.
TAHO is infrastructure software that decomposes workloads into smaller units and routes each one to the resource best able to run it.
Where TAHO fits
An insert, not a replacement. TAHO slots between the tools you already run and the hardware you already own — your orchestration and your hardware stay exactly as they are.
Above TAHO
Your orchestration
Kubernetes · SLURM · Ray · vLLM — unchangedTAHO
Decompose · route · execute
Routes each unit of work to the resource that fitsBelow TAHO
Your hardware
NVIDIA · AMD · Intel · TPU · Trainium — no lock-inArchitecture
What it actually is
The Magnetic PeerMesh is a decentralized execution fabric. No central scheduler decides where work goes. Peers exchange state and claim work themselves.
Nano-services
The unit of work.
Small enough to fill the gaps that whole-workload placement leaves empty..ONCE Execution
Each unit runs one time.
No duplicate work, no lost work.TAHO Gossip Protocol
Peers exchange capacity state directly.
Routing survives node loss without a central control plane.
Background
Todd Smith is Co-Founder and CEO of TAHO Labs. He has worked across global infrastructure, company scaling, acquisition integration, and revenue operations. A recurring pattern in that work: as systems grow, the constraint shifts from adding capacity to using the capacity already in place. That's what TAHO Labs is built to address.
Snap
Operated through rapid growth, infrastructure expansion, and acquisition integration including Bitstrips.Docker
VP of Operations as ARR grew from roughly $60M to $175M in about 15 months, while scaling operational systems and revenue operations.TAHO Labs
Co-founded TAHO Labs and took the Magnetic PeerMesh from architecture to signed enterprise POCs and a filed patent portfolio.Capacity is table stakes. Fit is the edge.
- Capacity remains necessary, but the advantage shifts toward systems that make capacity usable.
- As workloads span CPUs, GPUs, accelerators, cloud, on-prem, and edge, the layer beneath orchestration becomes more consequential.
- Buyers will evaluate execution efficiency, not only infrastructure spend.
- The teams that fit work to machines more effectively will get more output from the hardware they already have.
Where the field is converging
NVIDIA · DynamoCo-locating prefill and decode on one GPU “leads to inefficient resource use”; disaggregating the phases lets each be optimized and assigned independently.Read sourceGartnerFrames AI infrastructure as deliberate workload placement — matching training and inference to the environment that fits across hyperscalers, neoclouds, on-prem, and edge.Read sourceAnyscaleSingle-container packaging forces CPU and GPU stages to scale as one unit, guaranteeing low utilization; argues for disaggregated, multi-stage execution.Read source
In the press
Yahoo Finance
Don't Trust Cloud Utilization, Says Todd Smith of TAHO Labs
Read articleCXO Dispatch
Todd Smith: Kubernetes Isn't Dying, but It's Breaking. Here's Why.
Read articleTechBullion
How Small Teams Are Redefining Scale: An Interview With Todd Smith, CEO of TAHO Labs
Read articleMSN
Leading Without an Office: Insights From Todd Smith, CEO of TAHO Labs
Read articleVideo appearances
YouTube
Harnessing High-Performance Computing: Todd Smith's Vision for TAHO Lab's Infrastructure Software
WatchYouTube
The TRUTH About AI's Real Value! Are Businesses Wasting $$$ on AI?
WatchYouTube
How AI is Changing Businesses (And What It Means for You)
WatchYouTube
From Woolly Mammoths to AI Mastery: Leadership, Innovation & the Future of Work
WatchWriting
Recent pieces on TAHO Labs.
Contact
For buyers, technical partners, and investors.
The best conversations are with people seeing the mismatch directly: underused hardware, rising coordination cost, heterogeneous infrastructure, and workloads that no longer fit the execution model.