Pattern recognition
Reads across the full DNAI™ incident history to find the chronic pattern behind repeat events.
Three cohesive modules. One perpetual loop. Value intelligence, action and improvement evolution – running continuously on your operation.
Datapro-V™ creates the live value intelligence layer. DNAI™ acts on it in near real time — tracking, predicting, and recommending fixes. DNOVA™ turns the continuous stream of insights into permanent process improvement and automation. The loop never stops. Neither does your operation’s improvement.
-
Datapro-V™
A live map of your operation- Value Streams
- KPI nodes
- Knowledge Graph
-
DNAI™
Root cause and recommended fixes, in real time- Track
- Sense
- Root Cause Analysis
- Predict
- Simulate
- Recommend Short Term Fix and Process Co-Pilot real-time
-
DNOVA™
Turns insight into permanent process improvement- Pattern recognition
- Process redesign
- Agentic Workflow design
- Orchestration
- Loop closure
DNOVA™ feeds the improved model back into Datapro-V™ — raising the baseline.
Datapro-V™: The DNA of your supply chain process
Datapro-V™ is our core proprietary patented framework and technology that grounds every decision the AI makes to the DNA of your process and KPIs that matter to your business.
Receive
Local step
ID: 0
Receive
KPI parameters 0
Putaway
Workflow
ID: 0
Putaway
KPI parameters 0
Pick · Zone C
Local step
ID: 0
Pick · Zone C
KPI parameters 0
Replenish
Local step
ID: 0
Replenish
KPI parameters 0
Pack
Workflow
ID: 0
Pack
KPI parameters 0
Your Process Value Streams….mapped to relevant node by node
Every step in your operation — person, system, machine — modelled as a live canvas. The VSM is not a diagram: it is the data anchor for every KPI calculation and every AI insight that runs on top of it.
Vendor Booking Confirmation
Local step
ID: 5
97.1%
Vendor Booking Confirmation
Rachel Patel 
Daniel Cooper KPI parameters 4
Time
Quality
Risk
Cost
KPIs - "Value metrics that matter" to your business, tracked on the value stream
Each node carries its own measurement — formula, data source, baseline, scope filter. The baseline defines what "good" looks like for that specific step. The traffic light reflects live deviation, not an industry average.
Pick · Zone C
Local step
ID: 0
Pick · Zone C
KPI parameters 0
Op #T-114 · temp
Zone C · Pick Area
SKU 4421–4438
Device 07
The knowledge graph of your process to make every decision and action grounded in specifics.
The Knowledge Graph stores the relationships between things: which teams own which steps, which assets are assigned to which locations, how processes depend on each other. DNAI™ reads from it when it answers any question.
The live canvas of your operation.
Real-time KPI monitoring at every node — from network level to individual step. The process map every DNAI™ insight is grounded in.
Model your operation step by step — nodes, connections, groups, cross-site dependencies. Assign owners, teams, machines, and applications to each step. Publication triggers KPI calculations and locks a versioned snapshot. Every change creates a new draft; every draft is auditable.
/ Edited with DNAI™ Copilot or built manually — your choice.
Time Quality Risk Cost Sustainability Customer Satisfaction
Each metric is configured per step — formula from the Datanoetic catalog, data binding to your warehouse columns, scope filter from your org structure. Results refresh every 5–30 minutes and appear as live indicators on the map.
/ Formulas and data lineage are fully transparent — you can inspect every calculation, every source column, every scope condition.
Every published VSM has a one-click Analytics view. See KPI trends over time, performance breakdowns by team, location, and process step, and the upstream/downstream dependencies of any deviation. No separate BI tool required.
/ Same VSM. Same data lineage. No exports, no separate dashboards to maintain.
Main workflow 1 Inbound & Receiving
Edit Flow Metrics Preview Live
EU Office
1 0 0 %
Gate-In Inspection
Local step
ID: 2
98.6%
Gate-In Inspection
Rachel Patel Daniel Cooper KPI parameters 3
Time
Quality
Cost
Unload & Dock Transfer
Local step
ID: 3
88.7%
Unload & Dock Transfer
Viktor Schultz 
Mei Tanaka KPI parameters 4
Time
Quality
Risk
1
Cost
Quality Check
Local step
ID: 4
96.2% 
DNAI
2 insights
DNAI
2 insights
Quality Check
Tomasz Nowak KPI parameters 3
Time
Quality
Risk
Putaway & Replenishment
Workflow
ID: 5
97.4%
Putaway & Replenishment
WM Warehouse
KPI parameters 3
Time
Cost
Sustainability
Group by:
KPIs Organisational units People
Filter by: Nodes Locations Organisational units
This week Daily Download
Map 8 sites Near real-time
97% Rotterdam WH 94% Hamburg WH 88% Warsaw WH 91% Budapest WH 78% Milan WH 96% Marseille WH 99% Madrid · EU Office 74% Istanbul WH
SLA %
100908070
Mon18 JanTue19 JanWed20 JanThu21 JanFri22 JanSat23 JanSun24 Jan
Rotterdam WHHamburg WHWarsaw WHBudapest WHMilan WHMarseille WHMadrid · EU OfficeIstanbul WH
Inbound Cycle Time mins
AggregatedBy node
3.33.23.13.02.9
Mon18 JanTue19 JanWed20 JanThu21 JanFri22 JanSat23 JanSun24 Jan
Freight Cost / Pallet EUR
AggregatedBy node
19181716
Mon18 JanTue19 JanWed20 JanThu21 JanFri22 JanSat23 JanSun24 Jan
Intelligence grounded in your operation.
Not a generic AI assistant. DNAI™ reads from your VSM, your KPI thresholds, and your Knowledge Graph — so every answer is specific to your process, your people, your data.
Tracks
Senses
Optimises
Acts Short-term fix today · long-term redesign via DNOVA™
Predicts
Simulates
KPI Guard monitors every published VSM continuously. An alert fires only when a deviation exceeds threshold and has persisted across at least two measurement periods and the data volume is sufficient — no noise, no false reds. Each alert appears as a badge on the process step where it is occurring, not in a separate dashboard.
/ The badge opens an Insight Card — not just a number, but a ranked list of contributing drivers with data lineage citations and a confidence rating.
/ Recommend-and-confirm. Every action awaits supervisor approval — explicitly not autonomous.
A persistent chat interface on every page. Ask a question in plain language — DNAI™ translates it into a query against your data warehouse and Knowledge Graph, returns the answer with source citations, and stays on context across turns. Use @ to reference any VSM, employee, org unit, or asset directly.
/ Every answer cites which data it used — so you can verify the reasoning, not just accept the conclusion.
Build and modify process maps through conversation. Describe what you want — "Add a Quality Check step between Receiving and Putaway and connect both" — and Copilot makes the changes directly on the draft map, describes every edit, and saves a rollback snapshot after each action.
/ Copilot works only on Draft maps. Published maps are locked — any change requires opening a new draft.
/ Available only on Draft maps. Recommend-and-confirm — every edit awaits your supervisor's approval.
Main workflow 1 Inbound & Receiving
Edit Preview Live
EU Office
1 0 0 %
Gate-In Inspection
Local step
ID: 2
98.6%
Gate-In Inspection
Rachel Patel Daniel Cooper KPI parameters 3
Time
Quality
Cost
Unload & Dock Transfer
Local step
ID: 3
88.7%
DNAI
New Insight
DNAI
New Insight
Unload & Dock Transfer
Viktor Schultz Mei Tanaka KPI parameters 4
Time
Quality
Risk
1
Cost
Quality Check
Local step
ID: 4
96.2%
DNAI
2 insights
DNAI
2 insights
Quality Check
Tomasz Nowak KPI parameters 3
Time
Quality
Risk
Putaway & Replenishment
Workflow
ID: 5
97.4%
Putaway & Replenishment
WM Warehouse
KPI parameters 3
Time
Cost
Sustainability
Main workflow 1 Inbound & Receiving
Edit Preview Live
EU Office
1 0 0 %
Gate-In Inspection
Local step
ID: 2
98.6%
Gate-In Inspection
Rachel Patel Daniel Cooper KPI parameters 3
Time
Quality
Cost
Unload & Dock Transfer
Local step
ID: 3
88.7%
Unload & Dock Transfer
Viktor Schultz Mei Tanaka KPI parameters 4
Time
Quality
Risk
1
Cost
Quality Check
Local step
ID: 4
96.2%
DNAI
2 insights
DNAI
2 insights
Quality Check
Tomasz Nowak KPI parameters 3
Time
Quality
Risk
Putaway & Replenishment
Workflow
ID: 5
97.4%
Putaway & Replenishment
WM Warehouse
KPI parameters 3
Time
Cost
Sustainability
1 0 0 %
Gate-In Inspection
Local step
ID: 2
98.6%
Gate-In Inspection
Rachel Patel Daniel Cooper KPI parameters 3
Time
Quality
Cost
Unload & Dock Transfer
Local step
ID: 3
88.7%
Unload & Dock Transfer
Viktor Schultz Mei Tanaka KPI parameters 4
Time
Quality
Risk
1
Cost
Quality Check
Local step
ID: 4
96.2%
DNAI
2 insights
DNAI
2 insights
Quality Check
Tomasz Nowak KPI parameters 3
Time
Quality
Risk
Putaway & Replenishment
Workflow
ID: 5
97.4%
Putaway & Replenishment
WM Warehouse
KPI parameters 3
Time
Cost
Sustainability
Cross-Dock Staging
Local step
ID: 6
96.2%
Cross-Dock Staging
Tomasz Nowak KPI parameters 0
Turn recurring incidents into permanent improvement.
DNOVA™ — the Process Intelligence & Orchestration Engine. Where DNAI™ fixes today’s incident, DNOVA™ reads the pattern across many incidents and makes the cause impossible to repeat — process-owner approved, codified into your operation.
Process redesign
Generates improvement proposals mapped directly to the steps on your VSM.
Automation design
Codifies validated actions into standing rules — every rule gated by human sign-off.
Orchestration
Coordinates cross-process and cross-function workflows once a change is approved.
Loop closure
Feeds the improved model back into Datapro-V™ — raising the baseline it measures against.
Same loop, two horizons.
| Attribute | DNAI™ | DNOVA™ |
|---|---|---|
| Mode | Recommend-and-confirm | Design-and-deploy |
| Acts on | A single event — today’s incident | Chronic patterns across many incidents |
| Produces | Near-real-time root cause + recommended fix | Systemic root cause + process redesign |
| Approval | Supervisor approves | Process owner approves a permanent change or automation |
| Outcome | KPI restored this shift | KPI eliminated — the same issue can’t recur |
20–35%
Batch release cycle
Modelled projection 15–25%
Batch rejections
Modelled projection 40–60%
Serialisation errors
Modelled projection Ranges are Datanoetic-modelled projections based on the precision lift from node-level root cause vs. dashboard alerting. Calibrated to your value stream during the first 30 days.
5–15%
Throughput per node
Modelled projection 10–20%
SLA breaches
Modelled projection 3–8%
Cost per unit handled
Modelled projection Ranges are Datanoetic-modelled projections based on the precision lift from node-level root cause vs. dashboard alerting. Calibrated to your value stream during the first 30 days.
3–5%
In-stock rate
Modelled projection 5–12%
Inbound throughput
Modelled projection 15–25%
Fulfilment cycle
Modelled projection Ranges are Datanoetic-modelled projections based on the precision lift from node-level root cause vs. dashboard alerting. Calibrated to your value stream during the first 30 days.
Built for AI from day one — not retrofitted onto it.
Legacy supply-chain software and generic AI copilots bolt intelligence onto architectures that were never designed for it. Datanoetic was built AI-native in 2024 — the intelligence layer, the process model, and the action engine are one system.
How legacy & generic AI works
Bolted on, after the fact
- AI retrofitted onto 20-year-old architectures, or an LLM wrapper with no process context.
- Batch analytics that show what happened — rarely why, never in real time.
- Answers in industry averages, blind to your specific operation.
- Black-box outputs you can’t audit or trace to source.
How Datanoetic works
AI-native, end to end
- VSM + Knowledge Graph built to your process before go-live.
- Near-real-time root cause with ranked drivers, cited to your data.
- Cross-value-stream reasoning — inbound to outbound, one model.
- Full data lineage on every answer; audit-logged, tenant-isolated.
Four categories, one built for your operations.
| Capability | Legacy SCM SaaS | BI / Dashboard | Generic AI Copilot | Datanoetic |
|---|---|---|---|---|
| AI built for your operation | generic model | none | industry averages | VSM + KG per customer |
| Real-time root cause | batch | shows what, not why | none | ranked drivers, cited |
| Near real-time agentic action | workflow only | none | generic tasks | DNAI™ recommend-and-confirm |
| Process improvement & orchestration | manual consulting | none | none | DNOVA™ — continuous loop |
| Auditable AI outputs | limited | none | black box | full data lineage |
| Regulatory-grade traceability (Pharma) | module-level | none | none | audit-logged, tenant-isolated |
| AI-native architecture | retrofitted | none | LLM wrapper | built AI-native (2024) |
| Perpetual improvement loop | none | none | none | Datapro-V™ → DNAI™ → DNOVA™ loop |
Connects to your stack. Stays in your tenant.
Read-only connectors to WMS, ERP, TMS, IoT, and T&A systems. Tenant-isolated BigQuery layer. Every data source is bound explicitly — nothing is inferred or assumed.
- WMS wms_picks · wms_quality
- ERP erp_orders · erp_inventory
- TMS tms_shipments · tms_otd
- IoT device_events · scan_confirm
- T&A shift_roster · attendance
Your existing systems stay
Datanoetic connects to what you already use — warehouse management, ERP, transport management, IoT sensors, time and attendance. Connections are read-only. We never write to your source systems; we read from them and materialise KPI calculations inside your isolated tenant.
Your source systems on-prem SaaS
Your tenant DNAI™ reasoning in tenant
BigQuery layer isolated
KPI views materialised
Knowledge graph your entities
DNAI™ reasoning in tenant Your data never leaves your tenant
Every organisation runs in a fully isolated BigQuery tenant. KPI calculations, Knowledge Graph data, and DNAI™ reasoning all run inside your boundary. No cross-tenant data sharing, ever.
First Pass Yield traced
100 × AVG( fpy_flag )
Cited in · KPI Guard #147
96.4% baseline 96.2%
Every calculation is traceable
Every KPI formula shows its source column, scope filter, and refresh interval. Every DNAI™ output cites the data it used. Every KPI Guard alert carries a confidence rating and data lineage. Nothing is a black box.
Managed, not self-install.
Ready in 12–16 weeks. First value in 30 days. Implementation is managed by Datanoetic — we scope your VSM, connect your data, configure your KPIs, and deliver your first real DNAI™-explained incident in week four.
- Scope & map
- Data connect
- KPI thresholds
- First value
See the platform on a real scenario. 30 minutes. No commitment.
We’ll show you Datapro-V™ live, run a KPI Guard alert on a mapped scenario, and walk through DNAI™ Chat and Copilot on real data — including a batch-release scenario on a sample pharma VSM if that’s your world.