The context layer for the model-driven era
Your world is changing faster than your ability to understand it. Pometry's time-aware context graph gives humans and AI a live, evolving feed of reality – so you can see hidden risks, trace decisions, and act with confidence.
Trusted by
armasuisse
Syntheticr
DeepFlow
Micron
Los Alamos National Labs
Tether
Snowflake
armasuisse
Syntheticr
DeepFlow
Micron
Los Alamos National Labs
Tether
Snowflake
armasuisse
Syntheticr
DeepFlow
Micron
Los Alamos National Labs
Tether
Snowflake
The only context graph with time built-in
Pometry builds a living model of the systems you care about, giving decision-grade context to leaders and AI.
A live feed, not a snapshot
The only graph system with time as a native dimension, enabling you to see how data changes over time.
Memory and context for AI
Plug any LLM into your temporal graph. Our neuro-symbolic engine grounds AI in real, evolving data.
Your data, your servers
A 10MB binary that runs on servers, edge devices or behind air-gaps. No re-platforming required.
From install to insight
What takes competitors 6 months, takes us 2 weeks. Capable of processing 3M edges per second.
HOW IT WORKS
From data to decision-grade context in weeks
Three steps to a living model of your organisation. No data migration, no re-platforming, no six-month implementation.
Installation
Install a 10MB binary on your infrastructure. Servers, edge devices, air-gapped machines - wherever your data lives, Pometry runs.
Mapping
Map data (from Jira & GitHub to internal systems & blockchain ledgers) into a temporal context graph in days, not months.
Understanding
Ask questions in natural language; explore systems visually; or build analytics with Python APIs & a temporal algorithm library.
Proven where it matters most.
Pometry's temporal context graph is trusted by global enterprises, governments, and leading research institutions to surface what static tools can't.
Transformation
Large programmes generate thousands of risks that static governance cannot see. Pometry surfaces hidden failure modes (dependencies, bottlenecks, avoidable cancellations) that derail delivery. A recent pilot uncover 100s of millions of reclaimable value for a Tier 1 bank.
AI & Agents
LLMs hallucinate because they lack temporal context. Pometry's neuro-symbolic engine grounds models in a living graph so AI can understand what's changed, why it's changed, and what to do about it. Winner of the BIS Innovation Analytics Challenge.
Financial Crime & Blockchain
Static monitoring misses evolving patterns. Pometry reveals collusion networks, UBO chains, and behavioural sequences as they evolve - whether in traditional transaction networks or blockchain ledgers. Trusted by leading financial & digital asset institutions.
The evidence speaks for itself
$300M
In value delivered for a single programme.
100,000s
Employee days identified as reclaimable.
2 weeks
From install to decision-grade findings.
Latest articles
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Analytics
The hidden failures of transformation
Large organisations today have more delivery data than ever. And yet, major programmes still drift. There is a mismatch between what transformation leaders can see and how transformation systems actually behave...
February 2, 2026
5 minutes
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Analytics
Why delivery optimisation is making transformation worse
For more than a decade, large banks have invested heavily in improving delivery. Agile at scale, lean governance, value-stream management, cloud tooling, and increasingly sophisticated PMOs were introduced with a clear aim: make transformation faster, cheaper, and more predictable. In many respects, this worked...
January 14, 2026
4 mins
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Analytics
The Missing Link for AI Agents: Why a Native Temporal Graph is Non-Negotiable
The recent OpenAI Cookbook on “Temporal Agents with Knowledge Graphs” has provided a brilliant blueprint for the next generation of AI: agents that don’t just answer questions, but reason over time, understand evolving contexts, and maintain a persistent, accurate memory. The cookbook perfectly outlines the what and the why – and the need to systematically update and validate a knowledge base, perform multi-hop retrieval, and resolve temporal conflicts.
August 27, 2025
3 min 52 sec
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Analytics
Prisoners Dilemma and advanced Graph analytics
Have you ever wondered when it’s better to cooperate versus when you should just look out for yourself? This is one of the oldest questions in human interaction, and a famous concept from game theory helps explain it perfectly: The Prisoner’s Dilemma.
February 16, 2022
2 min 23 sec
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Analytics
Are Temporal Graphs Relevant to You?
If you’re exploring the world of data analytics, you’ve seen the power of graphs. By modelling your data as a network of entities (like people or products) and their relationships (like transactions or interactions), you unlock powerful insights that are easy for anyone to understand. But what if you’re only seeing a single frame from a feature-length film?
January 9, 2022
2 min 3 sec
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Analytics
The Graph Model vs. The Relational Model
Graphs have attracted significant interest in recent years. In this blog, we dive deeper into the differences between the graph model vs the relational model to get a clearer view on when you might use one over the other.
October 18, 2021
1 min 26 sec
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Analytics
The Alan Turing Institue: The Dizzy Potential of Dynamic Graphs
We're thrilled to be featured in a recent article by The Alan Turing Institute that highlights the power of our temporal graph system, Raphtory, in overcoming the limits of traditional data analysis.
December 1, 2020
58 sec
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Analytics
Holistic Network Analysis Over Time
For every real threat, compliance teams are buried under an avalanche of false positives. This “alert fatigue” is more than just an annoyance; it’s a critical vulnerability and a massive operational drain. Investigators waste precious time chasing ghosts born from monitoring systems that lack context, while sophisticated, genuine threats risk being lost in the noise. The key to solving this isn’t more alerts, but more clarity.
1 min 34 sec
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Analytics
Reduce False Positives
For every real threat, compliance teams are buried under an avalanche of false positives. This “alert fatigue” is more than just an annoyance; it’s a critical vulnerability and a massive operational drain. Investigators waste precious time chasing ghosts born from monitoring systems that lack context, while sophisticated, genuine threats risk being lost in the noise. The key to solving this isn’t more alerts, but more clarity.
1 min 41 sec
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Analytics
High-Performance Investigation at Scale
For an investigator, time is the most critical resource. Every minute spent waiting for a query to run is a minute a criminal has to cover their tracks. Unfortunately, legacy systems simply can’t keep up with the scale of modern data. The result is a slow, frustrating process where deep, exploratory analysis is impossible. To win the fight against financial crime, investigators need tools that operate at the speed of their own curiosity.
1 min 40 sec
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Analytics
Advanced Behavioural Sequencing
Modern financial criminals are choreographers of complex schemes. They don’t rely on a single, obvious action but on a carefully orchestrated sequence of events designed to appear legitimate in isolation. From smurfing and structuring to synthetic identity fraud, the true criminal intent is hidden in the pattern, not the individual steps. To defeat these adversaries, you must learn to read the grammar of their crimes by analysing the sequence of their actions over time.
1 min 26 sec
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Analytics
Unified Temporal Engine for AI
Your most valuable insights are not hidden in a single database; they are scattered across dozens of disconnected systems. Customer data lives in one silo, transaction logs in another, and event streams in a third. For an AI application, trying to make sense of this fragmented landscape is like trying to read a story with every other page torn out. To unlock true intelligence, your AI needs a unified, historically aware foundation.
1 min 18 sec
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Analytics
True Semantic Understanding Across Time
Semantic search was a monumental leap forward, allowing us to find information based on meaning, not just keywords. But it operates in a flat, timeless world. It can find what you’re looking for, but it often misses the deeper context of why it’s relevant now. True understanding, the kind that drives accurate decisions, requires a fourth dimension: time.
1 min 21 sec
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Analytics
High-Performance Context at Scale
An AI application can have the most sophisticated reasoning capabilities in the world, but if it’s waiting for data, it’s useless. In today’s high-velocity environments, the value of an insight diminishes with every passing millisecond. The challenge is that as datasets become larger and more dynamic, the context retrieval process becomes a crippling bottleneck, leaving your AI feeling perpetually slow and a step behind reality.
1 min 35 sec
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Analytics
Evolving Context Beyond Static Vectors
Vector embeddings have given AI applications a phenomenal ability to understand semantic meaning at a single point in time. But this is like understanding the world through a series of disconnected photographs. While each photo is accurate, the story - the narrative of how things change and connect - is lost between the frames. For AI to achieve true contextual understanding, it needs to see the whole movie, not just the snapshots.
1 min 29 sec
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Analytics
Dynamic Risk Scoring
A traditional risk score is a snapshot in time. It’s a static assessment based on current data that becomes outdated the moment it’s calculated. In the fast-paced world of financial crime, this is a critical vulnerability. Bad actors can escalate from low-risk to high-risk in minutes, not months. To combat this, you need a dynamic risk scoring model - one that lives, breathes, and adapts in real-time as new data arrives and behaviours change.
1 min 52 sec
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Analytics
Unmasking Collusion & UBOs
Sophisticated criminals and sanctioned individuals are masters of concealment. They hide their influence behind complex webs of shellcompanies, trusts, and nominee directors, making it nearly impossible fortraditional KYC and due diligence checks to identify the Ultimate Beneficial Owner (UBO). To break through this wall of obfuscation, you need to go beyond static ownership charts and reconstruct the entire, evolving history of control and interaction.
1 min 26 sec
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Analytics
Agentic AI Framework Support
The future of AI is collaborative. We are moving beyond monolithic models to sophisticated agentic frameworks – teams of specialised AIs working in concert to solve complex problems. But like any high-performing team, they need a single, reliable source of truth. Without a shared understanding of reality and its evolution over time, these AI teams, just like humans, descend into chaos, working with conflicting data and drawing contradictory conclusions.
1 min 36 sec
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Analytics
Advanced GraphRAG with Temporal Depth
Standard RAG applications are powerful, but they have a blind spot: time. They can retrieve what an entity is, but they can't understand its journey. Pometry’s temporal graph foundation empowers your AI to understand the crucial context of when and how connections form, change, and dissolve, transforming flat, static answers into rich, dynamic narratives.
1 min 18 sec
Discover what's hiding in your data.
Book a 20-minute demo to see why leading enterprises are replacing static snapshots with a live feed of reality.
