AI Server is a private AI server for teams. It runs chat, document search, image generation, speech and vision models on hardware you own, and serves them through one OpenAI-compatible API to your staff, your apps and your own software. Prompts and documents stay inside your network.

AI Server architectureClients on the left call AI Server over its API. AI Server runs local engines and, only if an operator configures them, cloud providers. The licence server receives activation only.AI Suite appsdiscover the serverAI Clientthin client on each deskYour code and toolsOpenAI SDKs, agentsAI Serverkeys · governance · auditLocal engineschat · embeddings · imagesSpeech and visionTTS · STT · detectionCloud providersoptional, operator-setLicence serveractivation · weekly leaselicence only
One AI Server serves AI Suite apps, AI Client and your own code. Models and engines run on the server; nothing passes through Software Tailor.

The problem it solves

Teams want AI assistants, document search and transcription. The common options each have a cost:

  • Cloud AI services send company data to a third party and charge per use, indefinitely.
  • AI on every laptop needs powerful laptops, downloads multi-gigabyte models onto each one, and gives IT no control.
  • Building your own AI platform needs specialist engineers to assemble, secure and maintain it.

AI Server is the packaged alternative: install it on one capable machine (or a cluster), and everyone uses it.

What you get

CapabilityWhat it means for the business
One API for chat, search, images, speech and visionExisting OpenAI-based tools and code work by changing an address
AI Suite apps and AI ClientReady-made desktop apps for writing, documents, translation, transcription and more, using the server
API keys per person and appAccess you can grant and revoke, with usage per key
Governance (Commercial)Rate limits, quotas, budgets, content rules, approved models, signed audit log
AI Gateway (Commercial)Grow from one server to a farm of up to 25 with one address, failover and safe upgrades
Runs anywhere you doWindows app, Docker, Kubernetes, Azure and AWS marketplaces

Who it is for

  • Small and mid-sized organisations that want AI on their own terms without an AI engineering team.
  • IT departments that need one controlled service instead of unmanaged AI tools on every desk.
  • Developers and integrators building AI features into internal systems or products.
  • Organisations with data rules — legal, finance, healthcare providers, public sector, research — that cannot send documents to a public AI service.

Editions at a glance

FreePro PersonalPro Commercial
WhoOne person on one computerPersonal, household, hobby and educational useBusinesses and organisations
ServesIts own computerYour networkYour network, with governance and gateway
PriceFreeUS$9.99 / monthUS$49.99 / month per server

Details, team packs and annual prices: editions and pricing.

What it takes to run

  • Hardware: a computer you already own for a pilot; one workstation with a modern GPU for a team; more servers behind a gateway as use grows. See scaling and sizing.
  • People: an IT generalist installs it in an afternoon. No machine-learning expertise is needed: models are downloaded and run by the server.
  • Ongoing: the Windows app updates through Microsoft Store; containers update by pulling a new version.

Next steps

  1. Try it free on one computer: install on Windows.
  2. Estimate value: business case.
  3. Review risks with your security and legal teams: risk and compliance.
  4. Size servers and seats with the deployment planner.

Questions

Is AI Server a cloud service? +

No. It is software you run. Software Tailor does not host your AI or see your data.

How is AI Server different from AI Suite? +

AI Suite is a set of desktop AI apps that can run models on each PC. AI Server runs the models centrally so many people and apps share them; AI Client is the lightweight desktop app for using a server.

Can we start small? +

Yes. Start free on one computer, move to Pro Personal or Commercial when other people need it, and add servers behind a gateway when one machine is not enough.