See your entire network at once.
Supply chains are deep, multi-tier graphs. TuringDB traverses supplier, warehouse, and route relationships in real time, and versioned snapshots let you compare how the network changes and where risk moves over time.
Get in touchModel suppliers, plants, warehouses, and routes as one connected graph and query it in real time. Multi-hop traversals surface bottlenecks, redundant links, and cheaper paths that stay invisible in spreadsheets and relational joins, so planners can rebalance the network before costs compound.
Most teams can see their tier-1 suppliers; the failures start at tier 3. Graph traversal walks the full dependency chain in milliseconds to expose single points of failure and concentration risk, and versioned snapshots let you replay how your exposure evolved as the network changed.
Mirror your physical operation as a living graph: every site, shipment, lot, and dependency, updated as events land. Query the twin in milliseconds to trace any product from source to destination, and branch it Git-style to simulate disruptions or recalls without touching production data.
These are example use cases. If your use case isn't listed and you'd like to know whether it's feasible and how it would work, get in touch.
Accelerate discovery on biological graphs.
Biology is a network. TuringDB models pathways, targets, and patient data as one connected graph, so research teams reason across millions of relationships in milliseconds and version every result for reproducible, auditable science.
Get in touchRepresent cells, tissue neighbourhoods, and signalling as a multilayer graph to predict how a drug will behave in an individual patient biopsy. The spatial relationships that drive response are structure a flat table can't hold, and columnar traversal keeps whole-tissue queries interactive instead of overnight.
Build causal graphs linking drugs, targets, pathways, and outcomes to find synergistic combinations and separate responders from non-responders. Traversals that used to take hours return in milliseconds, so hypotheses are tested as fast as they're formed, and every analysis is versioned for reproducible science.
Reason across millions of interactions between genes, proteins, diseases, and compounds to rank targets on evidence-backed paths. Sub-millisecond multi-hop queries make automated, exhaustive prioritisation practical at a scale conventional systems can't reach.
These are example use cases. If your use case isn't listed and you'd like to know whether it's feasible and how it would work, get in touch.
Decision advantage at machine speed.
Intelligence and operations are relationship problems. TuringDB reveals connections across entities and sensors in milliseconds, with full versioning so every assessment is auditable and every change is traceable.
Get in touchFuse entities, events, communications, and sensor reports into a single graph and traverse it in milliseconds to reveal the networks and patterns flat databases miss. Native versioning keeps every assessment auditable: you can show exactly what was known, and when it was known.
Model infrastructure, identities, and traffic as a graph to trace attack paths and lateral movement as they unfold. Millisecond multi-hop queries make true real-time monitoring of critical systems possible, and zero-lock reads never stall while new events stream in.
Link assets, terrain, routes, and infrastructure into a geospatial graph of the operating environment. Traverse it live to assess reach, dependencies, and lines of communication, and branch scenarios Git-style to war-game options without disturbing the live picture.
These are example use cases. If your use case isn't listed and you'd like to know whether it's feasible and how it would work, get in touch.
Model risk the way it really is: connected.
Money moves through networks. TuringDB traverses transaction and counterparty relationships in real time to catch risk as it forms, and native versioning keeps a complete, point-in-time audit trail for every regulator.
Get in touchFraud lives in relationships: shared devices, addresses, mule accounts, and circular flows. Real-time network analysis traverses transaction chains in milliseconds to expose rings and suspicious patterns while the payment is still in flight, not in tomorrow's batch job.
Assess counterparty and portfolio exposure across the full web of ownership, lending, and settlement relationships. Graph traversal reveals concentration and contagion paths that stay invisible in tables, and it's fast enough to re-run with every material market move.
Native, Git-style versioning records every change to the data: who changed what, and when. Reconstruct any point-in-time state instantly for auditors and regulators, with complete lineage built into the database instead of stitched together from logs.
These are example use cases. If your use case isn't listed and you'd like to know whether it's feasible and how it would work, get in touch.
Ground your models in connected knowledge.
Agents reason best over structured relationships. TuringDB serves knowledge graphs to LLMs and agents with sub-millisecond, multi-hop retrieval, and zero-lock concurrency keeps that knowledge live as it updates.
Get in touchGround retrieval in a knowledge graph instead of loose text chunks: entities, relationships, and provenance the model can actually follow. Graph-native retrieval returns richer, more precise context and cuts hallucination, with sub-millisecond traversals keeping latency out of the response loop.
Turn scattered documents and databases into one queryable, versioned knowledge graph for your organisation. Zero-lock concurrency lets agents and people read while pipelines write, so the knowledge base stays live and current without ever blocking a query.
Give models a structured world to reason against instead of free text. Multi-hop traversals across millions of entities let an LLM verify claims, resolve entities, and follow chains of evidence in real time, and versioned graphs make every answer reproducible after the fact.
These are example use cases. If your use case isn't listed and you'd like to know whether it's feasible and how it would work, get in touch.
Answer compliance questions instantly.
Compliance lives in relationships and history. TuringDB maps entities, ownership, and obligations as a graph for instant answers, and versioning records who changed what and when for a defensible audit trail.
Get in touchMap companies, subsidiaries, directors, and beneficial owners across jurisdictions as one connected graph. Multi-hop traversal untangles ownership chains and surfaces conflicts of interest in milliseconds, replacing days of manual cross-referencing.
Ask compliance questions of the full relationship graph and get answers instantly, not after a batch job. When rules or corporate structures change, versioned snapshots show exactly how your obligations shifted, ready well before the audit deadline.
Model contracts, clauses, parties, and obligations as a connected graph rather than isolated documents. Every modification is versioned, recording who changed what and when, so you get a defensible audit trail and instant answers about which agreements a change touches.
These are example use cases. If your use case isn't listed and you'd like to know whether it's feasible and how it would work, get in touch.