ABOUT ANTHUS
About us
We are an AI engineering company that builds and operates self-aligning AI systems (custom models, agent harnesses, and evaluation loops with a human in the loop) for teams that need them to keep working in production.
- Revenue
- Function
- Agent
- Decision
One system, four shifts: on-premises, cloud, serverless, and now AI. We kept it running through each.
01 / History
Since 2007
We came together as a team as the business expanded, and we have worked cohesively for more than a decade.
2007
The platform starts running
Ryan Porter becomes CTO of Venue Driver, a hospitality technology startup, and builds and runs all of its technology. The system has been in continuous operation since.
2009
A world tour
Ryan builds an event ticket sales system for a Tiësto world tour. It sparks a business that generated up to $64 million annually.
2014
Hakkasan Group
Hakkasan Group acquires Angel Management Group together with Venue Driver, which Angel Management Group had created as a spin-off. The business grows from a tiny startup into a department of a large multinational. We integrate third-party platforms, including Salesforce, Marketo, Salesforce Marketing Cloud, Mailchimp and Paytronix, and build an enterprise data warehouse.
2021
Tao Group Hospitality
Under Tao Group Hospitality and its parent, Madison Square Garden Entertainment, the platform passes rigorous audits and moves from a monolith to a serverless distributed architecture, then is handed to the next team with no business interruption.
2024
Anthus
The team that has worked together for more than a decade turns full time to the intersection of software and artificial intelligence. The Anthus name is the only new thing.
2026
The night we stopped being the loop
In February, the nightly routine of pasting “Continue.” into agent sessions before bed breaks the chat way of working. The story is below.
Ryan Porter founded the business and leads Anthus. Read his story →
02 / Track record
What held up
An impeccable record in reliability and security, kept through every technology shift: cloud computing, serverless, and now AI.
What it was
A bespoke ticketing, VIP table reservation and guest list system: serverless (AWS Lambda and Amplify), event-driven (SQS queues), and operationally mature.
What it integrated
Tao Group’s in-house loyalty system, Madison Square Garden Entertainment’s ITSM (ServiceNow), and a bespoke data warehouse and business intelligence system.
Everything else
Massive DDoS attacks, primary database server failures, silent failures in third-party systems, and everything else you could imagine. We always kept the revenue flowing.
03 / Mission
What we’re here to do
Deliver reliable, secure, and efficient business solutions using collaboration between human and artificial intelligence in every aspect of development and operations.
We build systems that keep working when nobody is watching.
04 / Values
How we decide
- 01Prioritize solutions over tools
Products and services only deliver business value if you’re in the business of products and services. We’re in the business of solutions.
- 02Focus on business logic
The only code you should write is the business logic that solves real problems. Don’t waste time reinventing wheels.
- 03Continuously improve
Rapid, iterative change through CI/CD and DevOps, then let the systems improve themselves. Self-optimizing classifiers and self-steering agent systems get better from production feedback without waiting for an engineer to notice.
- 04Infrastructure as code
DevOps for infrastructure, MLOps and LLMOps for the models. Every part of a production system, including training runs and evaluations, should be created by code so it’s reproducible, not clicked together by hand.
- 05Optimize resource usage
Balance efficiency with cost-effectiveness. When intelligence is cheap, the goal shifts from conserving compute to conserving context and cognitive load.
05 / February 2026
The night we stopped being the loop
When we started using AI to write the code and make the decisions, the chat way of working broke under the volume. A person had to sit there keeping the agents going or the whole process stopped, and a person had to hold in their head what was happening across every parallel session in every project for every client, because nothing else did. The low point is on the record, like everything else we do.
Stupid new nightly routine that I never wanted: Pasting “Continue.” into Codex 20 times in a row before I go to bed, in four different sessions. I will look back at this like black and white television. Rotary phone dials.
So we stopped being the loop. We ran all of it on our own work first, in public.
Tactus
Names the three ways a person can be in the loop, supervised, unattended and asynchronous, and makes the third one programmable: an agent runs on its own and interrupts a human only at a decision point.
Kanbus
The memory that lets work move between Claude Code, Codex, or whatever comes next. We’ve held since 2023 that models are commodities.
Primus
The scorecard where reviewers correct a decision model’s verdicts and their explanations become policy.
06 / Now
How we build today
Cybernetic development
The AI era doesn’t remove the need for operational excellence, it raises the stakes. We use a cybernetic approach: clear intent, layered safeguards, and production feedback loops that continuously harden the system. Delegating the work turned out to be easy; observing it is the whole job.
07 / Clients
Who we work with
Product and engineering teams
Putting LLM agents or classifiers into production, not just prototypes.
Operations and QA organizations
That need AI to make judgments at scale while experts stay in control (the Call Criteria pattern).
Revenue-critical businesses
Where downtime, security incidents, and silent failures are unacceptable.
08 / Facts
Key facts
- Company name
- Anthus AI Solutions
- Type
- AI engineering and operations company
- Founder
- Ryan Porter
- Website
- anth.us
- Core offering
- Self-aligning AI systems: custom models, agent harnesses, and evaluation loops with a human in the loop
- Services
- LLM fine-tuning, agentic AI, MLOps and LLMOps, serverless architecture, AI-assisted operations
- Track record
- Team together for over a decade; revenue-critical platforms in continuous operation since 2007; a call-center QA classifier lab run on Primus for years, across hundreds of scorecards and millions of interactions
- Platform
- Primus, an MLOps platform
- Contact
- anth.us/ryan
Questions
What does Anthus build?
Production AI systems that improve from feedback: fine-tuned classifiers, agent systems, and the evaluation and MLOps infrastructure around them. We also operate what we build.
How is Anthus different from a typical AI consultancy?
We are operators first. The team has run a revenue-critical platform since 2007, through data center failures and DDoS attacks, before applying the same discipline to AI. We ship systems with human-in-the-loop feedback, not demos.
What is human-in-the-loop AI?
Experts review and correct the AI’s judgments, and those corrections become training signal. In the Call Criteria classifier lab, QA specialists guide the models this way, and the scorecards have improved through reinforcement learning from human feedback (RLHF) over years of production, across hundreds of scorecards and millions of interactions.
Do you only work with one model provider?
No. We treat models as replaceable components and design systems so a model can be swapped without rebuilding the business logic.
PRESS START
What can we develop and operate for you?
Even if you can’t yet say what you need. Working that out is part of the first month, and it’s often the most useful part.