AI made deciding easy.
Acting safely is the missing layer.

BI tells you what happened. RPA executes what you scheduled. AI copilots suggest. Plasma acts — deterministic, auditable, sovereign.

See Intelligence in action
The landscape in 2026

Four approaches. One goes all the way.

Retrospective
BI / Dashboards
Tell you what happened. You still decide and act. The human is the bottleneck.
Grafana, Dataiku, Power BI
Scheduled
Workflow / RPA
Execute what you scheduled. Can't react to the unexpected. Brittle when conditions change.
Zapier, Make, UiPath
Suggestive
AI Copilots
Suggest actions. Can't execute them safely. No audit trail. No policy enforcement.
ChatGPT, Copilot, Gemini
Autonomous
Plasma
Detects the situation. Selects the policy. Executes the decision. Logs the trace. Learns from the outcome. Deterministic, auditable, sovereign.
The missing step

Without action, data is nothing.

Traditional frameworks stop at comprehension. Plasma extends the chain.

Traditional frameworks stop here
DataRaw facts, multiple sources
InformationStructured, contextualized
KnowledgeCorrelations, patterns
→
Plasma extends the chain
DecisionWhat to do
ActionExecute & trace
LearnFeedback loop
↻ Action feeds back into data — continuously.

The system perceives, understands, decides, acts, and learns. A living system — not a static pipeline.

Every deployment

From any source to any decision.

Akiem, ZE Energy, Grand Musique Management, Lemissa — different worlds, the same shape. Your systems flow into Plasma; decisions flow back out.

SOURCES PLASMA ACTIONS Edge & IoTsensors · devices · telemetry Enterprise systemsERP · CRM · asset mgmt Markets & partnersAPIs · marketplaces Public dataweather · maps · open data Signalsingestion & events LakehouseData → Information→ Knowledge Cognitionreal-time intelligence Stabilizationpolicy · full trace Detectsituations as they happen Decideoptions under your policy Actor hand to a human Traceevery decision auditable
See it applied: Akiem · ZE Energy · Grand Musique Management · Lemissa
Trust through evidence

Authority transfer: how the system earns your trust.

01
Observe
The system detects situations alongside your team. Logs every decision it would make. Takes no action. Proves it sees what you see.
02
Propose
The system suggests actions. Your team validates. Trust builds from evidence, not promises. Every proposal traced and scored.
03
Execute
Your team promotes to Execute. The system acts under pre-approved policy. Full trace. Demote in one click if the situation changes.

Promotion is a policy decision, not a configuration toggle. Your team owns the boundary.

Sovereign by design

Your data. Your infrastructure. Your code.

EUPL Licensed
The source code is yours. Open-source under the European Union Public License. Audit, fork, extend.
Host Anywhere
Scaleway, OVH, Hetzner, on-prem, air-gapped. Your jurisdiction. CLOUD Act immune.
No Lock-in
Already have a data stack? Plasma integrates on top. Starting from scratch? Plasma is the stack.
Research & Method

Designed from research, not guesswork.

Plasma's architecture comes from an active research program (CIR) on trust in human-machine collaboration. We studied why naive generative AI fails to earn adoption in real operations — and designed Plasma to solve it.

Explicit boundary
The line between deterministic computation and generative interpretation is visible and traceable. No black box where it matters.
Calibrated trust
The system earns authority through evidence over time — not by configuration. One trusted decision at a time, never a leap of faith.
Contextual memory
The system adapts to your operations and evaluates signals relative to history — not in the abstract. It learns your context.

A research-backed platform — not another AI demo.

Dogfooding

We don't just sell Plasma — we run on it.

Plasma runs Skilld. Since 2018, our own operations — client projects, conversations, analytics, the recommendations our team acts on — run on the same open-source platform we deploy for you. Self-funded since 2012, no outside capital: the platform that builds the company is the one that runs it.

Real-time conversation analytics
Engagement, sentiment and risk on our own operations, scored as it happens — the Cognition layer we ship, pointed at ourselves.
Operational intelligence
Project, contribution and next-action signals our team relies on daily — Plasma's ontology applied to how we work.
Our own AI layer, in production
Talk — our Plasma assistant (MCP enabled), is in daily use — on our own infrastructure.

Same open-source platform. Same infrastructure ownership. No special version for us.

Read the full case study →