Glossary
Features that Optimize AI Efficiency and Reduce Token Spend
Connector Auto Scoping
Narrows the queries to the connectors that hold meaningful context for a specific investigation. This lowers AI spend while reducing noise and accelerating response time.
Context Awareness
Arms agents with context-specific insights so they can know what alerts and threat intel inputs matter to an organization’s specific risk profile, and which don’t.
Context Compaction
Summarizes the conversation history into a compressed representation, preserving the most relevant information without retaining every raw token exchanged.
Data Dictionary
As the index of all connected data sources, it offers a view of every dataset, field, and path across connectors, helping SOC teams understand what data is available and how to use it.
Persistent Memory
Our product learns from context and from experience. It can self-correct and self-heal, so previous events inform current developments, saving enrichment and investigation time.
Planning Mode, a.k.a. No Black Boxes
Enables SOC teams to know in real time what assumptions the AI is making, allowing analysts to guide and edit agent-led workflows before using tokens to embark on the wrong initiative.
Human-AI Collaboration
Human-AI SOC
Defines Andesite’s approach to AI-powered security in which SOC professionals delegate menial work and repetitive tasks to agents while putting humans at the helm. In this work dynamic, SOC teams oversee AI-driven workflows, assess threats, respond immediately, reduce risk, and focus on prevention.
Humans at the Helm
In Andesite’s Human-AI collaboration model, cyber defenders manage the SOC and supervise AI work. It does it by empowering SOC teams to configure their agents and playbooks, as well as to oversee and guide AI-driven automations. Our product automates triage, enrichment, investigation, and response. Using Andesite, cyber defenders can work at machine speed while overseeing evidence validation and making the critical decisions they are accountable for.
Humans in the Loop
While humans at the helm puts security professionals in charge, making the decisions and managing AI workflows and agents, humans in the loop defines the ground-level collaboration in which humans and agents interact within workflows.
Product Architecture
Decision Fabric
The Decision Fabric is the centerpiece of Andesite’s technology. This is the layer where disparate data sources are connected, organizational context is established, and actionable insights are made. It is engineered to be flexible and domain-agnostic, and adapts to customers’ use cases, tools, and workflows.
Modern Data Architecture
Our product is built on a modern, layered, and composable data architecture. Rather than tightly coupling data to the tools that analyze it, it separates the data layer from the analytical layer. It learns the data it is working with, then pivots and correlates quickly with the right context to determine which data is worth capturing. The result is an architecture that scales across large, federated organizations and analyzes data at or near the edge, in real time, without waiting for log ingestion.
NO ETL
ETL stands for Extract, Transform, Load; a common way of processing data from multiple sources by extracting and cleaning it to standardize the format before loading and storing it in a central repository, like a data warehouse. Andesite doesn’t need to extract, transform, and load data to operate at once with structured and unstructured data from multiple sources. That means no expensive data migration or extraction is needed, which avoids delays, reduces complexity, minimizes exposure, and ensures enhanced security.
Safe AI Architecture™
Andesite’s architecture protects customers’ applications and data:
- Adapts to customers’ use cases, tools, and processes
- Offers single-tenancy SaaS and air-gapped self-managed deployment options
- Protects access and identity security via IDP and CAC / PIV
- Provides guardrails around customer data – we do not train our AI with it
- Uses end-to-end encryption at rest, in transit, and in storage