AI cost assurance
The most cost-efficient setup for each step of your AI workload, kept there as the market changes.
Anchorlight AI is an AI cost assurance company, a European start-up based in Prague.
Get in touchThe problem
The model landscape changes every week
The AI model landscape is large and changes every week: new models, new prices, new versions. That makes it hard to run AI workloads efficiently and harder still to stay efficient, and easy to spend far more than the work requires.
What we do
Simulate, move, keep it there
Anchorlight AI simulates each step of a client's AI workload on its own data, moves it to the most cost-efficient setup that meets the quality the client requires, and commits to keeping it there as the market changes.
We measure not only average quality but how often and how badly each step can fail, design each setup to keep the serious failures rare, and on that basis aim to guarantee the cost of a unit of work, such as one answered customer email or one handled support ticket.
What it brings
For a client, this typically means AI that is 30 to 40 % more efficient (cheaper at similar quality, or better at similar cost)*.
Riding the progress of the market
The setup does not stay fixed: as better and cheaper models appear, they are tested automatically on the client's own work, and each step moves to them automatically once they hold its quality, so the client keeps riding the progress of the market instead of falling behind it.
Evidence of reliability
It gives the AI team evidence of how reliable each step is, which is often what a complex process needs to move past the pilot stage.
Less dependence
It means less dependence on any single model or provider.
* Illustrative, within the range we measured on two reference workloads built on public data. Not client results. ↑
The team
The methods insurers use to price risk, applied to the cost and quality of AI.
The founding team has built AI for large enterprises for over a decade, including production generative-AI systems in banking, insurance and pharma, and kept running into the same unanswered questions about cost and reliability.
Its founder began his career as an actuary, went on to build and sell one of the largest applied AI companies in Central Europe, and now brings the two together: the methods insurers use to price risk, applied to the cost and quality of AI.
Technology
How the parts fit together
Our technology has the following parts.
Simulation engine
Replays a client's real workloads with alternative models and settings before anything changes in production.
Quality lab
Scores the results against the client's own standard.
View of the model market
Continuously maintained, drawing on benchmarks and on our own measurements.
Adaptive router
Decides, from these results, which setup handles each step and, where it pays, each individual request.
How we work
From one workflow to further workloads
Assessment
We start with a short questionnaire and an assessment of one workflow. The client shares the telemetry it already collects, or we help set up the collection, and we show for each step what a different setup would do to cost and quality.
Live
What the client approves goes live with its existing AI gateway, or ours if it has none.
Kept current
From then on we keep it current and extend it to further workloads.
Forward-deployed engineers, throughout
Throughout, our forward-deployed engineers work with the client's team and help it use our technology at every stage.
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