About Infasia

We put a trustworthy AI workforce inside industry.

Infasia LLC designs, deploys, and operates agentic AI systems that take on labour-intensive, non-critical work, so organizations move faster, spend less, and free their people for higher-value work, without surrendering control of their data.

Mission

Infasia exists to put a trustworthy, controllable AI workforce inside the operations of industry. We design, deploy, and operate agentic AI systems that take on labour-intensive, non-critical work so that organizations move faster, spend less, and free their people for higher-value work, all without surrendering control of their data.

Vision

To become the default partner for industrial AI in our chosen markets: the company an operator turns to when it wants its own AI capability running on its own terms, the advisor it trusts to get AI right, the educator that up-skills its people, and the source of the AI products its market comes to rely on.

What we stand for

Five commitments that shape every engagement

01

Trust and control first

Your data, your agents, your terms. Control is designed in, not bolted on.

02

Augment, do not just replace

Agents take the drudgery so people move to higher-value work, supported by change management.

03

Proof over promises

We earn autonomy with measured results, not slideware. Shadow mode and ROI dashboards keep us honest.

04

Local depth

We win on local and on-premises deployment and on agents tuned to a real workflow in a real market.

05

Build the flywheel

Every engagement sharpens our methods, our tooling, and our proof, so the next one is faster and better.

The flywheel

Four pillars, each feeding the others

Education and consultancy open doors and build trust. Services delivers core value and deepens our expertise. Products, which we build and run on our own infrastructure, turn that expertise into recurring revenue. Every pillar strengthens the others.

How we deliver

Start from a real problem, earn autonomy through proof.

We deliver agentic AI on infrastructure the client controls: open-source models hosted locally or on-premises where data sensitivity demands it, cloud where it does not. Delivery is standardized, with a supervisor console and a live ROI dashboard. Where a client wants it, agents can be presented as a single named assistant orchestrating a team of sub-agents, but that is a delivery option, not the core of the offer.

Trust and Control

  • On-premises by default, with encryption and per-client isolation.
  • Role-based access with single sign-on and multi-factor authentication.
  • Least privilege per agent and human-in-the-loop approval gates.
  • An emergency stop and an immutable, per-agent audit trail.

Where we are building

A phased, deliberate market sequence

We prove the model where it is strongest, then expand step by step. Regulatory specifics shift quickly and are verified before we enter any market.

Want to put an AI workforce to work in your operations?

We would like to hear what you do and where the repetitive work piles up.