SPINCYCLE
Bind. Run. Hand off.
SpinCycle orchestrates search, observability, and recommendation workflows using diverse data sources that can shape-shift with your needs.
Workflows drift. Context silos. Signals get lost between systems.
AI workflows depend on context borrowed from a dozen upstream systems — streams, schedules, rule engines, audience data, model endpoints. Each of those systems changes on its own clock. Schemas shift by a tenth of a sigma. A data source quietly updates its field names. A model gets swapped for a cheaper one. The workflow still runs. The outputs still look plausible.
That is drift. Decisions downstream stop matching intent upstream, and the organization only finds out when a regulator, an advertiser, or an audience notices first. Traditional integration — point-to-point glue, bespoke adapters, nightly batch reconciliations — cannot catch it. It can only report the wreckage.
Chain them together so they cannot drift.
SpinCycle leverages MCP (Model Context Protocol) servers to bridge AI models and the external tools, databases, and data sources they depend on. Every module is signed. Every connection between modules is a bond with a schema contract enforced at the boundary. You control the order, the origins, and the organization of every workflow and the modules that compose it.
Modules reach out to local and remote data sources, to LLMs and SLMs, to demographic and first-party data you already trust. Standard APIs expose the results to your stack or a third-party. A dashboard lets operators compose chains, watch them run, and see — in real time — whether every producer and consumer is still aligned within bounds. Model-agnostic. On-prem, cloud, or hybrid, as the job requires.
Same grammar. Different problems.
Same engine, same vocabulary of signed modules and bonded chains. Swap the nodes, swap the outcome. Three M&E deployments, identical underneath.
Built for the control room first.
Media and entertainment is the primary wedge. Broadcast traffic and automation teams running live linear alongside CTV. Regional legal and compliance desks shipping the same master to Riyadh, Dubai, London, and São Paulo under four different regimes on the same day. Archive operations absorbing a second company's library after an M&A close and staring down a decade of untagged footage.
These problems look different on the surface and are identical underneath: context from many systems, converging on a decision, under time pressure, inside rules that cannot be guessed at. Bind the modules. Run the chain. Hand off a signal the downstream system can act on — or log, or escalate — with complete provenance.
The same grammar carries into neighboring industries, wherever high-stakes workflows span multiple data producers and consumers.
Your interface or ours.
SpinCycle exposes every bound chain as a standard API and as a native MCP server — so the results land wherever your team already works. Feed a downstream platform, trigger an automation in your existing stack, or talk directly to the orchestrator from any MCP-compatible client. No forced migration, no new dashboard your operators have to learn.
The platform stays model-agnostic. Bring the LLM, SLM, or specialist vision model that fits the job; swap it when a better one ships. On-prem, cloud, and hybrid deployments use the same orchestrator, the same signing, the same bonded chains — with hardware-level optimizations for the sustained, high-throughput inference that continuous video and document workloads actually demand.
Move workloads across the seam as economics and policy dictate. The interface to your downstream systems stays constant.
Talk to us.
Tell us the workflow that is drifting. We will show you what bound looks like.