Technology
Aletheron is built as three layers. Each is useful on its own; together they turn raw records into something a person can act on.
Data foundation
Everything starts with data we trust. We ingest from primary sources, normalise schemas, deduplicate, and continuously check for gaps and anomalies.
- Primary-source ingestion with full provenance for every record
- Analytical snapshots rebuilt daily for fast, reproducible queries
- Automated quality checks that block bad data before it reaches an agent
Agent layer
Specialised AI agents decompose a question, query the data, run models and challenge each other’s findings. Every conclusion carries the evidence that produced it.
- Multi-agent workflows with explicit tool use and structured hand-offs
- Model-agnostic: the best available model for each task, replaceable over time
- Evidence tracking from final answer back to individual records
Product layer
Insight is delivered where decisions happen: a web application, a timely alert, or an API your own systems can call.
- Web products served from a global edge network
- Alerts through the channels people already use
- APIs for teams that want to build on top of our data and agents
Engineering principles
Evidence over eloquence
A fluent answer is not a correct one. Agents must show their sources, and the product must make them easy to check.
Humans stay in the loop
Agents do the heavy lifting; people make the decisions. We design review points, not black boxes.
Boring infrastructure
We prefer proven databases and simple pipelines over novelty. Reliability is a feature.
Privacy as a constraint
Data minimisation is decided at design time, not patched in later.