Co-Intelligence Ecosystem
How people and AI work together
AI looks wider and faster. Human experts judge the results and take responsibility for them.
We connect people, AI, tools and knowledge into one flow that can be controlled, so each covers for the others and every result is checked.
How do people and AI actually work together? Reviewed
In one shared workflow, with approvals and records handled in a single layer above it.
The parts that work together
This is not a single platform. These parts work toward the same goals within the same workflow, and what we learn in real work builds up as security capability.
- People and organizations
Security experts; your development, operations, audit and decision-making staff; research and education partners.
- Specialist tools
Tools for attack, assessment, analysis and validation, used directly by people and also by AI agents.
- AI models and security agents
External, internal and local models, and role-specific security agents equipped with tools, knowledge, verification and collaboration.
- Shared coordination
A controlled layer that links tasks, status, context, results, evidence and approvals across everyone involved.
- Data, knowledge and playbooks
Knowledge bases, attack and defense techniques, playbooks, evaluation datasets and quality standards.
- Operation, control and verification
Roles and permissions, approval and stop procedures, reasoning and evidence, quality and safety evaluation, and policy compliance.
- Training and evaluation
Hands-on and scenario training, testbeds and cyber ranges, challenges and performance evaluation, where people and AI agents learn together.
- Services and partners
Services that combine experts, tools and AI, working alongside partners' technology and data.
One operating flow, from connect to improve
We don't simply add up what people, agents and tools can each do. We design them to work together in these six steps.
A model alone is not enough
What matters is not how strong a single model is, but running people, agents and tools as one.
Turn potential into shared results
Connect strong models, specialist tools, several AI agents and experienced people to reach results none of them could reach alone.
Keep constraints from lowering quality
Even where models are limited, breaking down tasks, running tools, shared knowledge, cross-verification and human judgment protect the quality and continuity of core work.
The model at the bottom can be replaced. The tools, data, playbooks, work history and human judgment above it stay, and keep improving.
Where this leads
Why we keep security capability independent of any one model or provider.
The five core areas and the research topics behind this way of working.
This page describes how we work. It is not a product or platform offered separately.