Analyse complex data
Help analysts and researchers connect structured, spatial, observed and contextual data without losing the path back to the evidence.
Core technology
42able Atlas
Atlas connects perception, world modelling, memory, reasoning, planning, decision-making and learning in a reusable software foundation for 42able research and products.
Current position
At a glance
- Area
- Technology
- Category
- Core technology
- Current status
- In development
- Stage
- Core technology and research
The research question
What this is—and why we are working on it.
42able Atlas is a modular AI research and engineering platform for analysing information and building systems that can perceive, remember, reason, plan and learn.
We are developing it because useful AI systems often need perception, memory, world models, reasoning, planning and learning to work together rather than relying on one model in isolation. Atlas gives those investigations a shared software foundation.
Atlas architecture
A modular system, not a single model.
Seven connected areas define the public architecture. The research tests both the modules and the information that moves between them.
- Perception
- World modelling
- Memory
- Reasoning
- Planning
- Decision-making
- Learning
What we’re building
The work behind the question.
The work combines AI research with the interfaces, data paths and evaluation software needed to test how modules behave alone and together.
- Modular components for perception, world modelling, memory, reasoning, planning, decision-making and learning
- Interfaces that let components exchange state and evidence without binding every experiment to one fixed architecture
- Software for running repeatable experiments, comparing behaviour and tracing how a result was produced
- A reusable platform on which 42able can test prediction, simulation, vision, language and geospatial research
Possible applications
Where this work could matter.
Atlas is designed as a reusable foundation for research and product engineering across several kinds of information-intensive work.
Reason across information
Combine retrieved evidence, memory and models of a situation so a system can examine relationships across more than one source.
Integrate AI into products
Give product teams modular AI and data components that can be tested and assembled around a defined task.
Support decision systems
Connect observations, forecasting and possible actions so decision-makers can inspect the information behind a recommendation.
Reuse intelligence
Provide other 42able applications with shared, evaluated building blocks instead of rebuilding the same intelligence for every project.
Current status
Where the work stands.
Atlas is in active development as 42able’s shared AI research and engineering platform. Its modular architecture and software direction are established, with current work focused on testing components, interfaces and evaluation methods.
Open questions
What we’re exploring next.
- Which interfaces let specialised modules cooperate without hiding where errors or uncertainty enter the system?
- How should memory and world models be evaluated across different tasks and timescales?
- When does a modular approach improve reuse, testing or traceability enough to justify its added complexity?
- Which results transfer between research domains, and which must remain specific to one problem and dataset?
Questions and collaboration
Explore the next question with 42able.
We collaborate where a research problem benefits from shared domain knowledge, relevant data and rigorous technical work.