Reasoning across every system your plant runs — generated against your own.
A machine stops at 02:40 AM. Your MES logs it and moves on. PragmaSpark knows the batch it was running is the last line on a key account's Friday order — and reasons about what to do before the morning shift walks in.
An agentic industrial platform. Causal reasoning, calibrated belief, look-ahead planning, golden-regime discovery — over a knowledge graph of your plant, with multi-site sovereignty. It reasons across every system you run, read-only and grounded, ratified by your people. And it deploys without the two-year integration tax — it generates itself against your systems, in weeks.
How a decision is produced — grounded, reasoned, ratified
Ground in the graph
One graph, not disconnected tables. Every fact traces to the record it came from.
Reason causally
Cause and consequence — what drives what, and what it puts at risk. Not correlation.
Weigh the move
Every option simulated against the model first. The consequence on the table before the recommendation.
Your people decide
The platform proposes. Your people decide. Supervised agency, never autonomy.
How it deploys — integration, generated not hand-built
Comprehend the estate
Reads your systems — schemas, catalogs, connectors. Builds the graph. Structure only, never your rows.
Build the platform
Generates the integration, the tools, the capabilities — fitted to your systems, not a template.
Prove it under test
Nothing ships unproven. Human-authored tests have the final say, not the model.
You review what ships
Arrives as reviewed pull requests. The platform generates; your architects approve.
One reasoning platform, across every system the enterprise runs
One foundation — knowledge graph, causal reasoning, calibrated belief — generated against each domain. Deep industrial stacks and generic transactional businesses, reasoning on one platform.
Enterprise Software
ERP · WMS · EAM · CRM — the systems of record that run the business.
MES
Manufacturing Execution Systems — the plant-floor system of record.
MOM
Manufacturing Operations Management — orchestration above MES.
Digital Commerce & Apps
Generic / transactional — any transaction-approval business.
Three things have kept enterprise software from reasoning. PragmaSpark solves all three.
No foundation to reason on. No capabilities that reason. And an integration that kills it on the way to the plant.
There's no foundation to reason on
Every system holds a piece. None holds the picture. One event ripples through systems from different vendors, different decades. The picture lives in the connections between them — and nothing reads across. The reasoning falls to people, stitching systems by hand. The enterprise records everything and reasons about nothing.
Even the analytics you have don't reason
Your reports say what happened. Nothing says why, what's coming, or what to do. Dimensional and sequential analytics slice the past into charts — silent on cause. And the capabilities that would reason — causal, predictive, self-improving, look-ahead — don't exist in the stack at all. Two dead ends: the analytics you have can't reason, and the ones that could were never possible.
Even if you built it, integration would kill it
The demo works. Deployment is where it dies. Getting it to run against systems never built to be read takes two years by hand — and buys exactly one deployment. The next customer's systems are different. Two years again, from scratch. That's why enterprise AI stalls at customer two. The reasoning was never the bottleneck. The integration was.
One platform that reasons — generated against your own systems.
A foundation that reasons. Twenty-one capabilities on it — standard analytics reborn, plus capabilities that never existed. A factory that generates the whole thing against your systems.
The reasoning foundation
A knowledge graph reads every system as one. A frontier reasoning model reasons over it. Your systems, connected into one typed graph — asset, work order, batch, order, account. Not a search over text — a walk over structure, grounded in the record every fact came from. The foundation the enterprise never had. Read-only from the start, and never a second system of record — your running systems stay exactly as they are.
Twenty-one capabilities, two kinds
Your standard analytics start reasoning. And capabilities that never existed become possible. Dimensional and sequential — reborn on the graph, reasoning about the past, not just describing it. Causal reasoning, calibrated belief, look-ahead planning, self-improving decisions, golden-regime discovery, multi-site sovereignty — none possible before there was a foundation. Not AI features bolted on. Your software, reasoning.
The product factory
The platform generates itself against your systems — proven, not promised. Reads your estate. Generates the graph and capabilities, fitted to your systems. Verifies every artefact under test. Delivers it as reviewed pull requests.
Proven: 18 capabilities, validated across five industrial datasets — public and synthetic. Under a day on a synthetic estate. A few weeks on yours — against an industry standard of two years, by hand, per customer.
What it is. How PragmaSpark uses it.
Every capability is delivered as an agentic AI capability — the agent reasons, the human ratifies.
How a capability comes alive.
Every capability works the same way. Built against your systems. Reasoned over the graph. Written back, so the next one starts smarter. Ask it anything, at any step.
The lifecycle
Build it
The agent proposes the model. You ratify it. It proposes, never signs; your sign-off is the only signature.
Produce the result
Generate the artefact — graph, bindings, causal structure. Then infer over it — beliefs, forecasts, plans. Generation stands it up. Inference makes it act.
Enrich the foundation
Nothing lands in a silo. Beliefs become edges. Motifs become facts. Cause attaches to structure. Every capability leaves the graph richer than it found it. The foundation compounds, run after run.
See it on the graph
Not a dashboard beside your data. Your data, carrying what the capability found.
The rules that hold on every screen
It proposes, never signs
A human ratifies every decision.
No naked percentages
Every number carries its evidence.
Screened before reasoning
Redirection and out-of-scope questions are caught, not answered.
Refusal is first-class
Thin data, out of scope — it refuses honestly, never guesses.
The foundation signs first
Nothing runs until identity is ratified.
Regenerated, never hand-patched
Systems change, the platform regenerates. No cruft.
Three problems. Three answers.
Here they are, in practice.
Example 1 — Reasoning across every system
- 1 A machine stops at 02:40 AM. The MES logs a downtime event.
- 2 On screen, that's the whole story.
- 3 The batch it was running? The order it completes? The account waiting on it? All in other systems.
- 4 Someone pieces it together in the morning, by hand.
- 5 By then the Friday delivery is already at risk.
- ✓ The stopped machine is one node on the graph.
- ✓ The platform reasons across it: this machine → this batch → this order → a key account, due Friday, penalty attached.
- ✓ The consequence surfaces before the morning shift arrives.
- ✓ The recommendation comes with its evidence and its confidence.
Example 2 — Analytics that reason, and capabilities that never existed
Your report says yield dropped on Tuesday.
- 1 That's the whole answer.
- 2 Why, whether it repeats, what to do — a day of guessing.
- 3 The report describes. It doesn't reason.
Your standard analytics, reborn
- ✓ The same report, now on the graph — it slices to where the drop lives: this line, this shift, this product.
- ✓ Every cell joins back to the graph, so a bad number opens its own context.
- ✓ The sequential lens shows the order — what ran before the drop, in what sequence.
Capabilities that never existed
- ✓ Causal reasoning finds the cause, not the coincidence — de-confounded from the control loops that hide it.
- ✓ Calibrated belief says how sure it is — with the evidence, and the sample count, behind it.
- ✓ Look-ahead weighs the fix before you make it.
Example 3 — Deployment without the two-year tax
- 1 The demo wins the room. The VP wants it. The CFO wants it.
- 2 Then the number lands: two years to hand-build the integration.
- 3 The pilot slips into next year's budget.
- 4 And the next customer? Two years again, from scratch.
- ✓ The factory reads the customer's estate — schemas, catalogs, connectors.
- ✓ It generates the integration and the capabilities, fitted to their systems.
- ✓ Every artefact is proven under test before it ships.
- ✓ It arrives as reviewed pull requests — in weeks, not years.
One platform. Three stages. Start where your trust allows.
See it reason on read-only first. Then let it act, generated against your own systems. Then run the whole platform inside your walls. Each stage adds; nothing is rebuilt.
The platform reasons; you see it.
The knowledge graph and the capabilities, live on your systems. Read-only. No code access. It reasons across every system, grounds every answer, cites every fact. Your people ratify every decision.
- Knowledge graph
- 21 capabilities
- Ask, grounded and cited
- Read-only
It acts, generated and proven, under your control.
The platform stops advising and starts acting, above the thresholds you set. The factory generates each capability against your systems; test-driven generation proves it before it ships. Every action logged, every override yours. Supervised agency, never autonomy.
- Supervised action
- The product factory
- Test-driven generation
The whole platform, inside your walls.
The same reasoning, the same capabilities, the same factory — re-hosted inside your network. Your data never leaves. Built for regulated, sovereign, latency-critical operations. Nothing changes about what it does. Only where it runs.
- On-premise reasoning
- The factory inside your walls
- Full data sovereignty
At a glance — what each stage adds
| Reason | Agency | Sovereign | |
|---|---|---|---|
| What it does | Reasons; you see it | Acts, under your control | Runs inside your walls |
| Access to your systems | Read-only · no code access | Generates against your code | Everything, on your network |
| The platform | KG + 21 capabilities | + product factory + TDG | + factory re-hosted on-prem |
| Who acts | Your people, on every decision | The platform, above your thresholds | The platform, sovereign |
| Your data | Stays in place, read-only | Stays in place | Never leaves your walls |
| Best for | Any customer — value first | Established / trusting teams | Regulated · sovereign · latency-critical |
Which one are you? Start where you fit.
Different customers come in at different stages — by trust, by domain, by how regulated they are. Find yourself below.
Value first.
You want proof before you commit. Start at Reason: read-only, no code access, the platform reasoning on your systems. See it work. Ratify its decisions. Decide from there.
Established teams.
You already trust the approach, or the relationship warrants it. Start at Agency: the factory generates against your code, proven under test, acting above your thresholds. Supervised agency, never autonomy.
Data can't leave.
Pharma, energy, critical infrastructure. Go Sovereign: the whole platform, factory included, inside your walls. Full data sovereignty. Sub-second, latency-critical.
Four domains, one platform
Enterprise Software
ERP · WMS · EAM · CRM
MES
Plant-floor system of record
MOM
Orchestration above MES
Digital Commerce & Apps
Any transaction-approval business
One platform. Three stages. Start where you fit.
Pricing follows the platform, not your effort. Start where your trust allows — grow as the value proves itself. Every stage, a conversation, not a checkout.
Reason
See it reason, read-only.
- The knowledge graph and 21 capabilities, live on your systems
- Read-only · no code access
- Grounded, cited answers
- Your people ratify every decision
Agency
Let it act, generated and proven.
- Everything in Reason
- The product factory generates against your systems
- Test-driven generation proves it before it ships
- Supervised action above your thresholds — logged, overridable, never autonomous
Sovereign
The whole platform, inside your walls.
- Everything in Agency
- Reasoning, capabilities and factory — re-hosted inside your network
- Full data sovereignty
- Sub-second, regulated, latency-critical
- Dedicated support
Reasoning that's grounded, controllable, and generated against your own systems.
Everything below comes from that.
It reasons on a foundation, not a pile of data
Your systems, connected as one knowledge graph. A frontier reasoning model works over the structure — a walk over what's connected, not a search over text. The foundation the enterprise never had.
Cause, not correlation
It doesn't tell you what moved together. It tells you what caused what — de-confounded from the control loops that hide it. The one thing generic AI can't do on your plant.
Your standard analytics start reasoning
Dimensional and sequential reports have always described the past. On the graph, they reason about it — why the number moved, not just that it did. Your existing analytics, reborn.
It generates itself against your systems
No two-year integration project. The factory reads your estate and generates the platform — under test, as reviewed pull requests, in weeks. The same deep integration, generated not hand-built.
No rebuild, read-only to start
Works over your existing Java, PHP or .Net stack through a read-only connection. No re-platforming, no data copy. Your running systems stay exactly as they are.
You stay in control
Advisory until proven. Every decision carries its evidence, its confidence, an audit trail and an override. Supervised agency, never autonomy — and it sharpens on your own ratified decisions over time.
See it reason on your systems.
We're onboarding early customers across all three stages — Reason, Agency, Sovereign. First-mover terms apply. Tell us where you fit and we'll set up a walkthrough.