We build the models and sovereign agents that operate the infrastructure layer — storage, compute, data, networking — using the latest open-weight models running on your cloud. For infrastructure and cloud providers launching AI products of their own.
For GPU clouds, storage vendors and sovereign cloud providers.
A product you can sell means owning the model, the cost curve and the data path.
Your "AI product" is a proxy to a model you rent. Every feature is gated by another company’s rate limits, pricing and roadmap.
Fine-tuned open-weight models served on your own GPUs. You set the SLAs, the versions and the price.
Margins evaporate the moment usage scales, and a vendor price change rewrites your unit economics overnight.
Inference cost is your hardware cost. Metering and margin instrumentation are built in from day one.
Every request leaves your cloud. For regulated and sovereign customers, that is a dealbreaker before the demo starts.
Models and agents run inside your VPC or region. No audio, prompts or documents transit an external service.
AI that operates the infra, agents that run on it, and the wrapper that turns it into a product.
AI that operates storage, compute and data
Autonomous systems that run on your infra
Turn the capability into something you sell
Our work is the middle band — fine-tuned models and sovereign agents — bolted onto the infra you already run and exposed as a product surface your customers consume.
Nothing in the first two stages calls an external API. Data never leaves your infrastructure’s boundary.
Four stages, fast, with working software at every one.
We map your infra layer, your customers, and where AI creates a product — not a science project. Feasibility and hardware sizing before a line of code.
Models tuned for your storage and compute layer, plus agents that run autonomously on your cloud. Latest open-weight models, fine-tuned, served on your GPUs.
Multi-tenant isolation, usage metering, billing hooks, a white-label console and API — the capability becomes something you can sell.
Full source, IaC, fine-tuned model weights and runbooks. Your team operates and extends it; nothing licensed back.
Launches an inference-plus-agent platform product on its own fleet — customers deploy fine-tuned open-weight models and agentic workflows without leaving the provider’s cloud.
Embeds anomaly detection and intelligent tiering models directly in the storage layer, sold as a premium data-management tier.
Ships an AI copilot for its console and a compliant, in-country inference product built entirely on open-weight models.
Working software, documented systems, and a team that can extend them.
Open-weight models fine-tuned and optimised for your hardware, with throughput and latency SLAs.
Autonomous and customer-facing agents running inside your cloud, with guardrails and audit trails.
Multi-tenant, metered, white-label — console, API and SDKs your customers can consume.
Per-tenant usage, GPU cost, latency and error dashboards, wired for billing and margin.
The parts that decide whether an AI product survives real scale.
Open-weight base models fine-tuned on your data and served for throughput: tensor and pipeline parallelism, continuous batching, paged KV-cache, speculative decoding, and quantisation (FP8 / INT4) sized to your GPUs. Autoscaling tied to queue depth, not guesswork.
Agent runtimes with deterministic tool schemas, retry and compensation logic, and hard guardrails on actions that touch infrastructure. Every step is logged with inputs, outputs and the model version that produced it, so operations stays auditable.
Per-tenant isolation at the namespace, model and data layer. Noisy-neighbour protection through fair-share scheduling, per-tenant rate limits and quota, and signed API keys scoped to a single tenant’s resources.
Token, request and GPU-second metering per tenant, exported to your billing system. Dashboards for latency percentiles, error budgets, cache hit rates and — the one that matters — gross margin per tenant and per product.
A cloud or infra company with no AI product yet, that wants one built to sell.
Model selection and fine-tuning, serving stack, agent framework, multi-tenant product wrapper, console and API, deployed on your fleet.
A launch-ready, metered AI product in weeks — with the source, weights and IaC handed to your team.
An established platform that wants models and agents inside its current storage, compute or console layer.
Non-invasive integration: models embedded in the existing data path, agents wired to your control plane, no disruption to live customers.
A new premium tier or capability on a product you already run, instrumented for margin from the start.
“Superteams brought clarity to an extremely complex distributed architecture problem. They designed and shipped a production system that cut our latency and infrastructure overhead in half.”
David Myriel“Superteams actually understands the technology. They come in, read the room, and produce work that holds up to scrutiny from our engineering team.”
Dan ShalevYes. Models are served on your GPUs (NVIDIA or AMD), agents run in your cloud, and nothing calls a third-party API. That is the point — a product you can operate and resell without a dependency you do not control.
You cannot build a resellable product on a per-token API you do not own — the margins, the data residency and the roadmap all sit with the vendor. Open-weight models fine-tuned on your data give you the economics and the IP.
vLLM serves a model. We build the models that operate your infra layer, the agents around them, and the multi-tenant product wrapper — isolation, metering, billing, console — that makes it something customers can buy.
Tenant isolation, usage metering and billing hooks are part of the build. You plug in your billing system; we instrument usage, GPU cost and per-tenant margin.
The serving stack is built to swap base models. You move from one open-weight release to the next by re-running the fine-tune and evaluation pipeline, not by rebuilding the product.
You do — source, IaC, fine-tuned weights and runbooks, handed over with no licence-back. Pre-built modules that speed the build stay our IP and are licensed to you; your custom code and data stay entirely yours.
Book a 30-minute strategy session. We’ll map where AI creates a product on your platform, size the hardware, and tell you exactly what an engagement looks like.
No commitment · direct discussion with a Principal AI Solutions Architect
