Threat feeds, incident history, asset inventory, identity data, and control mappings live in separate tools. LangOptima ingests the security data you already hold and connects it into a single queryable knowledge base, so analysts trace an alert to everything it touches in seconds, each hop cited back to its source.
The approach behind MITRE D3FEND, the semantic-web knowledge graph companion to ATT&CK, mapping defensive techniques to the threats they counter so coverage gaps become visible.
An alert names an asset and a signature, not what it connects to. In many security teams, learning whether it matters still means pivoting across the SIEM, the asset database, the identity store, and past tickets by hand.
A SIEM alert names an asset and a technique, not the systems it can reach or the identities that can access it. Analysts assemble that context by hand, across several consoles, on every alert.
Feeds describe techniques and indicators in the abstract. Mapping them to your own assets, identities, and prior incidents is manual, so intel rarely reaches the analyst as “this affects these specific systems.”
The map of which asset depends on which, who can access what, and which incident touched what lives in senior analysts' heads. Every investigation rebuilds it from scratch.
LangOptima ingests the security telemetry and records your organization already holds, including asset inventory, identity and access data, incident history, and threat-intelligence feeds, and structures what is inside them: assets, identities, vulnerabilities, techniques, and the relationships between them. Public frameworks like MITRE ATT&CK already model attacker techniques as a connected graph; the same shape, applied to your own environment, is what turns an alert into an answer. It sits above your SIEM, asset database, and intel platforms without replacing them, so a question that once meant pivoting across tools becomes a single traversal, with each source attached.
Modern AI can structure a great deal on its own. Where it stops is the meaning specific to your organization: the concepts, rules, and relationships that make your business yours, and where its real value lives. We structure that layer with you on open, world-standard semantics, not a proprietary schema, so the graph reflects how you operate and stays yours: no vendor lock-in, portable to whatever you run next. More on the structure beneath it →
Asset inventory, identity data, incident history, and threat feeds unified at the semantic layer. Nothing moves. Nothing is replaced.
Traverse from a technique to every asset it can reach, from an identity to everything it can access, from an indicator to every past incident it appeared in. Connections no single console shows.
“What does this alert actually touch, and is it already covered?” answered in seconds, with the records to back it. For responders and threat-intel teams alike.
Every analyst triages with the full environment map behind them, so junior responders scope incidents that used to wait for the one person who knows how everything connects.
Representative scenarios of how security teams apply a knowledge graph over their own environment. Illustrative of the pattern, not published client references.
A security team connects its asset inventory, identity data, and incident history in a knowledge graph. When an alert fires, the analyst traverses from the affected asset to everything it connects to and everyone with access, each hop citing its source, instead of pivoting across five consoles.
A feed reports a technique. With the environment modeled as connected data, the team asks which of their assets and identities it could reach and which controls already cover it, and gets the answer as one query, traceable to the underlying records, instead of a manual cross-reference.
However complex the data landscape underneath, the engagement itself stays simple.
You don't have to boil the ocean. Start with a single business context and prove it there. Once that foundation is laid properly, the same connected data tends to open opportunities in other departments, so the next team builds on the work already done rather than starting from zero.
We ingest the content and data you already hold, straight from the systems you already run. Nothing is replaced. Your teams keep working where they work today.
A scoped 8–12 week pilot structures your first decision context. Your domain experts contribute the knowledge; we do the engineering.
You start asking the questions, and every answer carries a citation back to the source, so you can check it yourself.
A 30-minute conversation about your security data landscape: which systems hold your assets, identities, incidents, and intel, and which question a connected view of them would answer first. No deck, no pitch.
The same connected-data approach, applied across sectors. Explore another industry.