The operational data platform you'dbuild yourself,if you had time for it
Bring your assets, processes, and measurements into one connected picture. Open source, deployable anywhere, and routinely a tenth of the cost of proprietary systems.
Median time from first deployment to production signal.
100%
Source available. Yours to run, read, audit.
Why teams adopt it
Built for engineering-ledoperators, and the agents they run
Most operations teams aren't short on data. They're short on a shared understanding of what it means, and access to it.
IntelliStream unifies assets, processes, and measurements into one model, so every question becomes one view instead of five. And the code that runs it is yours to read, run, and change.
The substrate your AI needs
AI models get sharper when they know which asset a reading came from, which process it serves, and which events coincided with it. We don't build the agents; we build the context layer underneath them, and the MCP server they reach it through.
A reported figure, a KPI, a 3 a.m. variance — every number has a production trail leading back through every transformation to the raw signals it was computed from, with data quality flags intact. Audit-ready by default.
Open source (AGPL-3.0). Deploy in your cloud, on-premises, or in air-gapped environments, with a European-hosted managed option for operators who need sovereignty guarantees US-hosted competitors can't offer.
Not a discount, but a different cost structure. No enterprise sales floor, no proprietary storage, no eighteen-month services engagement bundled into the quote. You pay for the platform and our time, not for the machinery that usually surrounds it.
The questionsasked every quarter,and never answered the same way twice.
Operations teams ask these every quarter. Most stacks can't answer them in one place, so the answers come from a meeting, a spreadsheet, and the senior engineer who remembers how the systems connect.
One query - compliance
Where did this regulated number come from?
Show me every shift report that contributed to last quarter's reported emissions figure, including which readings were filtered out and which had errors at the source.Every reported figure traces back to its raw signals, with data-quality flags intact. The audit trail is the query.
I need to take this piece of kit offline for maintenance. Which downstream services depend on it, and which customer or regulatory commitments are affected during the window?Assets, the functions they perform, and the business context around them — all linked. You see the full radius before you commit.
Which measurements are drifting from expected service levels, which processes do they support, and which revenue, customer obligations, or regulatory requirements depend on them?One model. Asset-age, contracts, and dependencies in the same place. Exposure becomes a quarterly query, not a project you commission once.
IntelliStream builds the shared model underneath, assets, processes, events, and the relationships between them, so every AI system you build or deploy is working from the same connected picture of your operation.
The agents get smarter
Models query a unified context graph instead of stitching together a dozen integrations on each call.
The answers get defensible
Every output is grounded in traceable inputs. Your auditor and your engineering team look at the same trail.
The infrastructure stays yours
Source available. Self-hostable. Portable.The substrate doesn't lock you in to anyone, including us.