From two-person startups to Fortune 500 platform teams — builders are pointing their AI computer at real infrastructure and shipping faster than their roadmaps assumed possible.
Acme's platform team had spent eighteen months wiring together a homegrown developer portal, an LLM gateway, an MLOps platform, and two third-party observability vendors. The total cost of ownership was approaching seven figures annually — before headcount.
In Q1 of 2026 they stood up the AI computer on a dedicated tenant at desktop.acme.com, mapped their SSO and audit pipeline in two weeks, and migrated 600 internal developers onto a single prompt-driven surface.
By the end of Q2, the platform team had retired four of the five legacy systems and reduced infrastructure spend by $2.3M / year while halving the time-to-first-deploy for new engineers.
A handful of teams who let us tell their story. Many more are using the computer privately under their own brand.
"We went from 'we should fine-tune a model on our data' to 'we have a private API serving our customers' in one afternoon. Zero MLOps hires."Priya RamaswamyVP Engineering
"Uploaded raw 4K footage, asked for a streaming product, got a working player and a CDN. We're a 3-person company and we ship like 30."Marek HalászFounder
"It's like having a senior infra engineer on call for $20 a month. We launched our MVP without hiring devops at all."Anika ReinerCTO & co-founder
"HIPAA-scoped, SCIM-provisioned, dedicated infrastructure. Our compliance team approved this faster than any vendor we've evaluated in a decade."Daniel ChoHead of Platform Security
"We ran our entire QA pipeline overnight on a cluster of H100s. The agent provisioned, batched, retried, and gave us a Slack summary at 8am."Olov LindqvistEngineering Director
"Our entire newsroom switched to the AI computer for research. The cost of a typical investigation dropped from days to hours."Carla MendesEditor in Chief
The computer is generic by design. Teams adapt it to their stack on their first prompt.
Risk pipelines, fraud scoring, batch inference on transaction data.
Video pipelines, real-time newsrooms, archive transcription.
HIPAA-scoped infrastructure, clinical AI, document workflows.
Recommendation, search, product image pipelines, edge personalization.
QA automation, asset generation, edge multiplayer, anti-cheat.
Training clusters, simulation, on-device model deployment.
Internal AI computers, white-label desktop, SSO/SCIM, audit.
Sovereign deployments, FedRAMP-scoped, data residency.
Free to start. Pay only for the work the computer does. Take a quick look at the product, or open the computer and ask it to build something.