PLATFORM
The reality understanding layer
Point of Data continuously connects people, things, relationships, events, and history into one living model your agents can reason over.
01 / PEOPLE
People
Who are they?
Customers
Employees
Partners
Users
02 / THINGS
Things
What exists?
Products
Orders
Devices
Locations
Assets
03 / RELATIONS
Relationships
How are things connected?
Customer purchased product
Order belongs to customer
Device operates at location
04 / EVENTS
Events
What is changing?
Purchases
Updates
Transactions
System events
05 / HISTORY
History
How did we get here?
Previous behaviour
Past decisions
Historical changes
Build agents that understand situations
TODAY'S AI
“Where is my order?”
The agent searches the order database, customer records, and documentation. Then it composes
an answer. It does not know what the answer means.
TOMORROW'S AI
“Where is my order?”
The agent already understands the customer, the order, the delay, the history, and the
resolutions available to it. It explains, recommends, and acts.
Capabilities
Everything you would otherwise rebuild in-house — resolved once, at the infrastructure layer.
Entity resolution
One person, one product, one truth — across every system that names them differently.
Relationship inference
Connections derived continuously, not modelled by hand in a schema meeting.
Temporal state
Every entity has a past. Query what was true at any point in time.
Evolutionary neural memory
Purpose-built for the data density, context, and temporal tracking AI actually needs — memory that adapts as reality does, rather than a store that only grows.
Signal ingestion
Streams, webhooks, CDC, batch. 200+ connectors and a generic adapter.
Situation briefs
A compact, token-efficient brief instead of a wall of retrieved chunks.
Provenance
Every fact traces to the signals that produced it, with confidence attached.
Policy & permissions
What an agent may know and may do, enforced at the layer, not the prompt.
Change subscriptions
Agents wake when reality changes, instead of polling for it.
The Stack
Four layers, built together rather than assembled. This is where the efficiency gains come from.
Read the architecture deep-dive →01
Autonomous Actors
Long-lived, stateful compute units with cryptographic identity. The execution primitive — not containers, not functions.
Stateful
Long-lived
Cryptographic identity
02
Evolutionary Neural Memory DB Service
A hypergraph of events, tags, and links with programmable search. Data evolution is a first-class primitive, not a migration.
Hypergraph
Events · Tags · Links
Programmable search
Event-sourced
03
Pod-OS Runtime
Bare-OS execution from edge IoT to HPC. POSIX-compliant, with service@actor addressing as simple as email.
Bare-OS
Edge → HPC
POSIX-compliant
service@actor
04
Zero-Trust Security
Actor-level isolation with encrypted data and encrypted messages. Trust is established per actor, never assumed from network position.
Actor isolation
Encrypted data
Encrypted messaging
See it on your own data
A 30-minute technical walkthrough with an engineer, not a sales deck.