Less routine. More craft.
Recurring tasks that keep piling up. Nobody enjoys them, nobody wants to spend their time on them. A local AI agent takes them off your hands.
From email triage and data extraction to analyses and drafting correspondence. A local AI agent handles the legwork, so your expertise lands where no one else can replace it.
Confidential data doesn't belong in someone else's data center. It belongs on your desk. The agent too.
Four steps to a working agent.
First conversation
Thirty minutes by video or phone. We talk about one specific process in your firm. At the end, you decide whether a blueprint is worth it.
AI Blueprint
A written feasibility and ROI analysis: architecture sketch, systems boundaries, and representative agent runs as the acceptance criterion. A self-contained value blueprint, tailored to your process. You can have me build it, or take it to another provider.
Build
Delivery and installation of the local hardware (a Mac Mini, a workstation, or a small server) at your premises. A tailored pipeline for exactly one use case, four weeks from signed scope. Acceptance when the defined agent runs complete cleanly.
Maintenance(optional)
Proactive monitoring, framework updates, push notifications on anomalies. New features are booked as a separate engagement.
Common questions.
What does an AI agent project cost?
The AI Blueprint is a self-contained deliverable at a fixed price. Implementation is quoted as a fixed-price package per use case, depending on data volume, hardware requirements, and pipeline complexity. Concrete numbers come out of the first conversation, once the process is qualified well enough for a reliable estimate.
How long does delivery take?
Four weeks from signed scope for one use case. The preceding AI Blueprint takes one to three weeks depending on complexity. Acceptance is formal once the pre-defined agent runs complete cleanly. Without that criterion, there is no sign-off.
What is an AI Blueprint?
A written feasibility and ROI analysis with architecture sketch, systems boundaries, and representative agent runs as the acceptance criterion. The blueprint is a self-contained deliverable: you can have me build it, or take it to another provider.
How is our data protected with an AI agent?
The agent runs on your own hardware on-site, such as a Mac Mini next to the desk or a small workstation. Confidential data never leaves the building. No telemetry, no outbound model-training pipeline, no cloud dependency at runtime. GDPR compliance is structural, not a matter of contract clauses with US hyperscalers.
Which use cases suit an AI agent?
Recurring tasks with a clear success definition: from email triage and data extraction through system integrations and research tasks to analyses, pre-screening, and drafting correspondence. It pays off when volume justifies dedicated hardware, and when you can supply a few representative cases against which the result is measured.
What infrastructure is required?
A Mac Mini or comparable device with 64 GB of RAM or more is typically enough. The exact specification is derived in the blueprint based on the chosen model size and data volume. Hardware procurement is included in the implementation.
About me.
In my day job, I'm a GenAI and Agentic AI project lead in the semiconductor industry. The same AI agents I build for you here, I bring into industrial-scale processes there.
With TensorPM I build AI agents for context-driven project intelligence — fully on the user's device, end-to-end encrypted, with the AI model of their choice. The same engineering foundation carries every client engagement.
Get in touch.
Thirty minutes, no commitment.
Video or phone.
By email: s.schwer@tensorpm.com
Current slot: open.