The accountability layer for autonomous systems
Reconstruct, explain, correct, and replay any event across agents, robots, and onchain systems. When systems act, you can answer for them - long after your logs would have aged out.
3+ years in production · 2B+ events per month · 1.3 GB/s sustained · SOC 2 Type II
Event ID
evt_01JWB2P4V2K11T6Q829H2
What happened
Invoice marked paid · NetSuite
State at the time
{ invoice_id: INV-7781,
status: paid,
amount: 1,250.00,
currency: USD }
Systems touched
N NetSuite S Stripe
Why you need it
If you can't answer that in one query, you don't have accountability - you have logs.
Every incident becomes an engineering project. Every audit becomes an archaeology dig. Every customer question becomes a week.
Without Continuum
You have logs.
One agent run. Its evidence scattered across five systems - each keeping only part, briefly.
Agent logs
Sampled
Different formats Partial timelines Missing context No accountability
With Continuum
You have the record.
The same run, the same systems - every event in one complete, correctable, provable history.
Agent
Complete Durable Correctable Queryable Replayable Explainable
It shouldn't. An answer should be one query away - and with Continuum, it is. See your own run on Continuum →
One record. Five powers.
All from the same complete record.
When something breaks, gets audited, or needs retraining, you don't need to launch an investigation or ask engineers to retrieve logs - you simply reference your Continuum record to get the answer.
See the complete, ordered story across every system.
The exact state seen when a decision was made - and what happened next.
The original stays visible; the correction points back to it.
A historical range replayed against updated logic, policy, or model.
The complete history through SQL, search, and APIs.
Jump to any moment
illustrative data
Not another dashboard. Continuum is the record itself - complete, ordered, correctable, and kept - so these five answers still hold months after the fact.
Who it's for
The blocker isn't capability - it's accountability: one provable record of what every system saw, did, and changed.
AI agents act across many systems. Continuum shows exactly what happened.
Agent run started
SFNS
Run failed mid-way
Problem: Money moved. The books disagree.
Continuum: Full run reconstructed, explained, and replayable.
From 2 Dec 2027, the EU AI Act requires logging like this for high-risk AI
Accountable outcome
ExplainCorrectReplayRobots and drones see the world. Continuum corrects the past and improves the future.
Robot missionEpisode recorded in fullCalibration issue found
Problem: Calibration was wrong. History is misleading.
Continuum: Corrections applied. Runs replayable.
Accountable outcome
CorrectReplayReprocessOnchain systems rewrite history under reorgs. Continuum makes it provable and auditable.
Transaction submittedReorg or mismatch
Problem: Reorg or mismatch causes settlement errors.
Continuum: Corrections tracked. Proven history.
Accountable outcome
ReconcileAuditProve"It solves the exact problem we have replaying real-world robot data as we build out our stack."
See it on your own data 30 minutes, engineer-led, no slide deck.
How it fits
Point your systems at Continuum and it just works: connect over the Kafka wire adapter or REST, keep your lakehouse and query engines exactly as they are, and your data stays in open formats with no lock-in.
AI agentsKafka wire adapter · REST
CONTINUUM
RECORD
One ordered history
QUERY
SQL & APIs
REPLAY
Any moment, again
No broker rebalancing. No partition gymnastics.architecture statement, not a durability guarantee
◎ Open storage (S3 compatible)
Open formats · no lock-in
Event formats
JSON · Avro · Protobuf
Access & tables
Arrow Flight · Iceberg · REST APIs
Physical AI
MCAP (Foxglove) · RRD (Rerun)
Storage
Open, S3 compatible · no lock-in
"I personally like that I can handle the data the way I want to do it. As long as I have all the data, if it's pre-processed, that's even better."
Already have a stack?
Observability, streaming, and warehouses each do their job. None of them is the record of what your systems did.
● kept as recorded · ○ lost · ▪ a copy, not the original
They all stay exactly where they are. Continuum is the layer underneath that remembers. See it on your own data →
Continuum wasn't built in a lab. It grew inside Moralis, keeping ordered, correctable history across 50+ blockchain networks - public data that rewrites itself and punishes every shortcut.
"This is probably the best thing I've seen so far, and I've been digging around this space since November last year."
Large events arrive whole, without claim-check workarounds or broker configuration changes. Fully decoded blockchain blocks with traces routinely run 5-15MB. Your history lives on low-cost cloud storage, so keeping all of it costs a fraction of what the same record costs on streaming infrastructure. SOC 2 Type II certified · self-hosted option available.
Technical pilot
No platform migration, no committee. Bring one workload; we'll map it with an engineer and show you what becomes possible.
We map it to Continuum.
Clear scope, outcomes, and next steps.
Start small. Scale with confidence.
30 minutes, engineer-led, no slide deck. Bring a run you couldn't explain.
FAQ
Continuum is the system of record for large, changing event data. It keeps one complete, ordered history of everything your systems do - AI agents, robot fleets, onchain data - and lets you reconstruct, replay, query, and correct any of it, anytime.
No. Observability tools sample traces for debugging and drop inputs and outputs by default. Continuum keeps the full, ordered, correctable record of what your agents saw, did, and changed - a record you can serve back, replay, and prove, not a dashboard.
Every event an agent produces - reads, decisions, tool calls, writes - lands in one ordered history. Corrections are recorded, not overwritten: the original stays, and everything built on it knows. That's accountability as infrastructure, and the record human oversight depends on.
The Act requires automatic event logging and human oversight for high-risk AI from 2 December 2027, with deployers retaining the logs. Continuum's ordered, correctable, replayable record is built to be that log.
No. Continuum plugs into the stack you already have - it speaks the same protocols your systems already use and stores data in open formats your existing tools can read. Connect a single workload and leave the rest untouched; your data stays in your own bucket with no lock-in.
Yes. Payloads up to 100MB arrive whole, natively: sensor frames, camera episodes, and complete agent runs - nothing split, trimmed, or reassembled downstream. Fully decoded blockchain blocks with traces routinely run 5-15MB.
Petabyte-scale history, billions of events per month, and sustained multi-gigabyte-per-second throughput - with the full history retained, ordered, and replayable rather than aged out.
