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AI Risk Intelligence · For Consumer & Retail

Product launches and supply chain projects are too important to manage by gut feel.

For Risk Managers · PMO Leads · BI Teams · Decision Makers

Aversight gives consumer goods and retail leaders AI-powered early warnings across their entire project portfolio.

Launch timelines, supplier quality, market risks — tracked in 10 different tools. Aversight unifies the intelligence without unifying the tools.

From mid-market teams to global enterprises. No minimum project count.

Take the Free Maturity Check →
734
FMCG professionals use our tools
2.3×
Avg project overrun
4h/wk
Saved on portfolio reporting
Read-only SOC 2 Type II ISO 27001 Your infrastructure Autonomous intelligence EU AI Act ready

Start with the dashboard. Zoom into every capability.

Nine real views — from the overall portfolio picture down to the Monte Carlo engine running underneath. Jump to what matters for your role, or scroll through the whole thing. Nothing hidden.

Jump to your role:
Aversight · Portfolio Intelligence
Synced 14 min ago
2
Critical >70
▲ +1
4
High 50–70
▲ +1
8
Watch 30–50
stable
6
Stable <30
▼ 2
58
Avg score
+3 WoW
€1.8M
Prevented YTD
4 projects
Score distribution · 20 projects
2
4
8
6
CriticalHighWatchStable
Risk heat map · Impact × Likelihood
A7
B3
D12
E4
F1
Likelihood →
Active alerts (3 new today)
Alpha-7 · overrun in 28 days
87% confidence · 2 min ago
Bravo-3 · vendor SLA at risk
71% confidence · 14 min ago
Delta-12 · velocity drop
64% confidence · 1h ago
+ 20 more this week
view all →
Portfolio Gantt · W14 — W21 · 5 active projects
W14W15W16W17W18W19W20W21
Alpha-7
!
87
Bravo-3
!
62
Delta-12
58
Echo-4
31
Foxtrot-1
22
Engine layers · live
Rules engine
12 active · 3 fired today
ML pattern
2 matches today · 1,240 trained
LLM recommendations
5 pending review
Monte Carlo · Alpha-7
P50 (median)€600K over
P5 (worst case)€2.4M over
Top driver: vendor SLA (+42%)
Live signal feed
06:14Jiravelocity −31%
06:02SAPPO delayed 17d
05:48ServiceNowSLA breach
05:30JiraCR-22 added
High-priority alert
Today · 06:14 CET
Budget overrun predicted — Alpha-7, 28 days ahead.
Portfolio: Grid Expansion North · Phase 3 · PM: J. Halvorsen

Budget burn on Alpha-7 has reached 1.4× plan at 47% timeline — well above the 1.3× threshold. Three milestones are overdue and the Lead Solution Architect is at 115% allocation. Pattern escalation_predictor matches 14 historical projects with similar overrun outcomes.

Signal contribution
budget_burn1.4× plan (thr. 1.3×)
milestone_drift3 overdue (thr. 2)
resource_conflict115% key role (thr. 100%)
open_risk_severityP×I = 16 (thr. 15)
87 Risk score · Critical band (>70) · pattern_match: escalation_predictor
Evidence trail
Alert ALT-2026-04-091
Rule ER-004 v2.1
1Rule fired
ER-004: Sustained velocity drop ≥ 25% over 3 sprints + ≥ 2 change requests open → predict overrun within 30 days.
2Raw data points
Jira: ALPHA7-2041, 2078, 2102 (velocity)
Jira: ALPHA7-CR-14, -19, -22 (change requests)
ServiceNow: INC-88412, INC-88733 (SLA breaches)
SAP: PO 4500-114-17 to -29 (delay log)
3Pattern match (ML)
Signature matches: Ostfriesland-2024 (€2.4M over), NordLink-2023 (€1.8M over), Bremerhaven-2024 (on-track, false match).
4LLM explanation
Claude Sonnet 4.6 generated the plain-language summary using only the data above. Prompt + output logged for audit.
Pattern match confidence 91%
Portfolio Gantt
5 active projects · Week 16 / 2026
synced from MS Project
+ Jira milestones
W14W15W16W17W18W19W20W21
Alpha-7 Grid Expansion
!
!
87
Bravo-3 Substation
!
62
Delta-12 Cable Lay
58
Echo-4 Smart Meter
31
Foxtrot-1 Windpark
22
Critical At risk On track ! active alert
Delivery · Middleware output
Where your intelligence lands
Standard formats
No migration required
📎
Power BI · Tableau · Looker
Push to dataflow / semantic layer. Refreshed daily. Your existing reports keep working.
Dataflow
Weekly email brief
HTML or plain text. Top risks, recommended actions, 2-minute read. Every claim cross-linked.
Email
📄
PDF · PPTX · DOCX exports
Branded, steering-committee-ready. Auto-translated EN/DE/FR/ES. White-label mode for consulting.
Files
🔌
REST API · Webhooks
JSON output with OpenAPI schema. Plug into any downstream system. Alerts pushed on threshold breach.
API
💬
Teams · Slack
Critical alerts only. Channel-routed by portfolio. No noise for low-priority signals.
Chat
Aversight is middleware: it sits between your sources and your outputs. No new dashboard to own, no data to migrate.
Active data connectors
Last scan 14 min ago
Jira Cloud
12,481 tickets indexed
SAP ERP
3,204 POs · 14 plants
ServiceNow
SLA + incident feed
SharePoint
Project docs, minutes
MS Project
218 active schedules
Outlook 365
Re-authing · 2 min
Excel / OneDrive
94 portfolio sheets
Azure DevOps
IT projects · 38 repos
Asana
Mid-market PM · 412 projects
Monday.com
Boards · pulses indexed
Notion
Docs, minutes, RAID logs
Google Workspace
Drive + Calendar + Gmail
Week 16 / 2026
To: Steering Committee
Portfolio at a glance
38 active engagements · 3 escalated · 1 new pattern detected
Client A — ERP rolloutScore 87
Client C — M&A integrationScore 74
Client F — Data migrationScore 69
• Client A: schedule go/no-go review before Friday; budget signal matches historical overrun pattern (91%).
• Client C: request updated staffing plan; velocity drop on workstream 2.
• Client F: verify cutover window; dependency on legacy CRM looks under-scoped.
Aversight Intelligence Engine · Reviewed: M. Okonkwo, Partner
What happens in your first six months
Week 1–2 · Live now
Read-only connections live
Jira + SAP + SharePoint connected. First portfolio scan complete. Baseline scores published.
Week 4
First rules-based alerts
Configurable thresholds active. Your first audit-ready alert hits your inbox — with full evidence trail.
Month 3
Pattern recognition kicks in
ML has enough history to detect cross-project anomalies. First predictive alert usually arrives here.
Month 6
Predictive intelligence
Escalation prediction at >85% precision on your portfolio. Weekly briefings fully automated.
Month 12+
Compounding intelligence
Your knowledge base is now your unfair advantage. Every completed project teaches the engine.
Scenario simulation · Monte Carlo
Alpha-7 · what-if risk score distribution
1,000 iterations
Updated 14 min ago
Budget increase+15%
0%50%
Milestone delay+10 days
0d30d
Resource loss1 person
03
Score 30 (stable) Score 60 (high) Score 90 (critical)
Best case (P95)
Score 48
Watch band · 5% probability
Median (P50)
Score 72
Critical band · 50% probability
Worst case (P5)
Score 89
Deep critical · 5% probability
P(critical) 72% under current inputs P(high): 93%
Rules engine · Deterministic layer
Signal weights & thresholds
LIVE
5 signals · weighted sum → 0–100 risk score · recalculates across portfolio on save
budget_burn28%
alerts when burn rate > 1.3× plan at <50% timeline
milestone_drift22%
alerts when ≥ 2 milestones overdue
resource_conflict20%
alerts when allocation > 100% on any key role
open_risk_severity18%
alerts when P×I ≥ 15 (high/critical risks open)
risk_staleness12%
alerts when risk register > 14 days without update
Pattern engine · Cross-portfolio learning
5 pattern types · detected today: 2
Retrained weekly
on your portfolio
escalation_predictor 91%
Projects trending to critical — 5+ consecutive days with score >50, later hit critical threshold.
Affects: Alpha-7, Bravo-3 · detected 06:14 today
budget_burn_correlation 87%
Burn rate >1.3× plan at <50% timeline, combined with elevated open risk severity.
Affects: Alpha-7 · historical matches: 14 similar projects
milestone_cascade 72%
2+ overdue milestones on same project — historically predicts 6-week schedule slip.
Watching: Delta-12 · 1 overdue, 1 at risk
resource_cluster 68%
Key role over-allocated >100% across multiple projects in the portfolio.
Watching: 3 solution architects · 4 projects
trend_correlation 54%
5+ consecutive rising days on score — early signal that later correlates with critical outcomes.
Monitoring: no active matches this week
Every match logged · false positives flagged by users feed back into the model · confidence improves with your portfolio history
AI recommendation · LLM layer
Alpha-7 · suggested action
Claude Sonnet 4.6
Grounded in
budget_burn rule (fired 06:14 · burn ratio 1.4×)
Pattern: escalation_predictor (91% confidence)
Evidence: 4 BudgetSnapshots · 3 Milestones · 1 high-severity Risk
Action
Schedule go / no-go review with Alpha-7 steering team; freeze change requests for 4 weeks.
Who
J. Halvorsen (PM)
+ Steering Committee
Timeline
Before Friday
(3 business days)
Expected impact
Prevent ~€1.8M overrun
based on 14 historical matches
Priority
HIGH
01

Your portfolio — at one glance.

One view. Every signal, every alert, every trend. The shape of your portfolio in under five seconds — before your first meeting. Click into any cell to see the raw evidence.

  • 4 live KPIs: open risks, escalations, portfolio score, prevented value YTD
  • Interactive impact × likelihood heat map
  • Top-priority alert feed (3 visible, rest on click)
  • Live signal stream from every connected system
02

Alerts you can act on before the meeting.

Every alert reads like a memo, not a log line. A concrete driver. A confidence score. A recommended action. Your inbox becomes a decision queue — not a problem feed.

  • Plain-language summary, 3–5 sentences
  • Numeric drivers tied to the underlying ticket, PO, or SLA row
  • One-click open into Jira, SAP, ServiceNow
  • Confidence scoring based on 14+ historical matches
03

Every alert is auditable to the source.

The EU AI Act is here. Aversight is built around transparent scoring. Every alert shows the rule ID, the raw data points that fired it, the historical pattern it matched, and the exact LLM output — with prompt and logs preserved.

  • Rule identifier + ruleset version for every alert
  • Direct citations to raw ticket, PO, SLA, or doc
  • Pattern match confidence + historical references
  • Full LLM prompt & output log for audit
04

Every project. Every milestone. Risk overlaid.

Your Gantt — but with intelligence baked in. Red bars are flagged projects. Flags mark active alerts. The “today” line moves itself. Drag-through any bar and Aversight pulls the raw ticket, PO, or minute behind the slippage.

  • Auto-synced from MS Project, Jira, Asana, or Smartsheet
  • Risk overlay recomputed every night
  • Dependency map: who blocks whom, with alert propagation
  • Critical path re-calculated on every new signal
05

Delivered into the tools your team already opens.

Aversight is middleware — it sits between your data sources and your outputs. No new dashboard to own. No data migration. Intelligence lands as standard formats in whichever channel your team actually uses every day.

  • Dataflow push to Power BI, Tableau, Looker (no custom visual, no ETL)
  • Weekly HTML email brief — every claim cross-linked to raw evidence
  • Branded PDF / PPTX / DOCX exports · auto-translated EN/DE/FR/ES
  • REST API + webhooks · OpenAPI schema · plug into any downstream system
  • Teams / Slack routing for critical alerts only
06

Signals from every system. Diverse by design.

The more signal diversity, the sharper the intelligence. Aversight reads from 8+ enterprise systems out of the box — tickets, ERP records, files, emails, calendars — and 40+ more via REST.

  • Pre-built: Jira, SAP, ServiceNow, SharePoint, MS Project, Outlook, Excel, Azure DevOps
  • Live status view: last scan, failed sources, row counts
  • Read-only service accounts — zero write access
  • SOC 2 Type II, ISO 27001, DSGVO-compliant by default
07

Board-ready briefs. In one click.

Every Monday, a one-pager lands in your inbox. Top risks. Client-ready language. Forward it to the steering committee without reformatting. White-label mode puts your logo on it for external engagements.

  • Branded PDF + editable PPTX & DOCX outputs
  • Automatic translation: EN / DE / FR / ES
  • White-label mode for client-facing deliverables
  • Every claim cross-linked to evidence for Q&A
08

Value in weeks — not quarters.

Typical engagement path: read-only connections in week two, first audit-ready alert by week four, pattern detection from month three, predictive intelligence by month six. Your practice bills faster because the intelligence is live earlier.

  • Week 1–2: baseline scoring across full portfolio
  • Week 4: first rules-based alert with full evidence
  • Month 3: pattern recognition + cross-project anomalies
  • Month 6+: predictive alerts at >85% precision
09

Under the hood: 10,000 futures per project, every night.

Every night, Aversight runs 10,000 Monte Carlo simulations per active project. Worst case, median, best case — with the drivers that move the outcome most, ranked. No black box: every assumption is surfaced, editable, and logged for audit.

  • P5 / P50 / P95 outcome distributions per project
  • Editable assumptions — see impact in seconds
  • Driver decomposition: which variable moves the outcome most
  • Export to Excel with full simulation log for audit
10

The rules engine: every alert is auditable code.

The deterministic layer. Every rule is written in plain language, version-controlled, reviewed by Legal and the AI Committee, and test-covered. You see exactly what would fire, why it would fire, and its historical precision — before you promote it to production.

  • WHEN / THEN syntax — readable by risk managers, not just engineers
  • Test-driven: every rule shipped with true-positive / false-positive history
  • Version-controlled: rollback any rule to any previous version
  • Approval workflow: Legal & AI Committee sign-off before PROD
11

Pattern recognition: your projects, ranked against history.

The statistical layer. Every active project is embedded into a 248-feature vector and ranked against 1,240 completed projects from your organization. When the closest historical matches overran — you get warned. When the match pattern was a false positive last time — the engine remembers and downweights it.

  • 248-dimensional project embedding, trained on your data
  • Top-5 historical matches surfaced with confidence + actual outcome
  • Feedback loop: false positives flagged by users adjust the model
  • Retrained weekly on your completed projects — compounds over time
12

AI recommendations — grounded, not generated.

The generative layer sits on top of rules and patterns. Claude Sonnet 4.6 turns the deterministic output into plain-language actions — but only using data the rules engine and ML already verified. No hallucination layer. Every prompt and output is logged for 7-year audit retrieval.

  • Grounded exclusively in rule output + pattern data + raw evidence
  • Plain-language action (“schedule go/no-go review before Friday”), not a summary
  • Full prompt + output logged for EU AI Act audit (7-year retention)
  • One-click Accept / Edit / Dismiss — every decision captured as training signal
Core challenges in consumer & retail

Why product launches and supply chain projects overrun.

01

Product launch timeline risks across markets

Coordinating product launches across multiple markets means dozens of parallel timelines. A delay in one market creates ripple effects across the entire launch calendar.

02

Supply chain transformation complexity

Supply chain digitization and restructuring projects involve multiple vendors, systems, and sites. Complexity hides risk until it surfaces as a missed go-live date.

03

Cross-functional dependency blind spots

Marketing, supply chain, R&D, and operations all contribute to launches — but dependencies between these teams are tracked manually, if at all.

What Aversight monitors

Four signals that protect your consumer projects.

🌎

Launch milestone tracking across regions

Monitors launch timelines across markets and flags deviations before they cascade.

🔗

Supply chain project interdependencies

Maps dependencies across supply chain transformation workstreams and flags critical path risks.

👥

Cross-market resource allocation

Detects when key resources are stretched across parallel market launches creating bottlenecks.

🚚

Vendor delivery timeline analysis

Tracks vendor commitments against delivery and flags emerging delays across the supply chain.

Powered by three autonomous intelligence layers: deterministic rules for auditability, statistical ML for pattern detection, and LLM for actionable recommendations. All three run continuously — no manual trigger required.

Early warning system

What Aversight alerts look like for consumer & retail.

⚠️
Product Launch APAC
Consumer€6.2M
72
⚠️
Supply Chain Digitization
IT€11M
58
💡
Packaging Redesign Wave 3
Consumer€3.8M
31
External data sources

Industry data that powers smarter risk models.

📈

Consumer confidence index

Demand forecasting data to anticipate shifts in consumer spending and launch timing.

📅

Seasonal demand patterns

Launch timing optimization based on historical seasonal peaks and promotional windows.

📊

Commodity price feeds

Packaging and ingredient cost tracking to model budget sensitivity to input prices.

📦

Retail inventory data

Distribution readiness monitoring to ensure shelf availability aligns with launch dates.

Scenario analysis

What does Aversight actually show you?

"What if APAC launch is delayed by 6 weeks?"

Best
Partial launch in 2 markets, +€0.4M revenue delay
Mid
Full region delay, +€2.8M revenue impact
Worst
Missed seasonal window, +€6.2M + competitive positioning risk
Trusted by leading brands

Used by teams at top consumer companies.

Global FMCG portfolios Consumer goods brands Retail & distribution Consumer packaged goods

"The first 6-week pilot showed us the system really works. We course-corrected two product launches early that would otherwise have significantly overrun their timelines."

— VP Supply Chain, Global FMCG Company

What this means for your career.

🚀

From “Department of No” to strategic advisor

Stop presenting threats that executives ignore. Start presenting intelligence that drives decisions.

📊

Executive-grade insights, not spreadsheet reports

Present risk data that your CFO understands and acts on — in 20 minutes instead of 4 hours.

💼

The tool that gets your budget approved

Show your leadership the ROI before you ask for investment. The numbers speak for themselves.

Calculate your ROI →

What Aversight means for your role

If you're an Analyst

You track supplier quality, launch timelines, and market risks in 10 different tools. Nobody sees the connections. With Aversight, you become the analyst who flagged the seasonal supplier risk that would have caused a stock-out during peak season — and saved the launch.

If you're a Risk Manager

Your launch risk assessments are a checkbox exercise nobody reads until something goes wrong. With Aversight, you present AI-scored risks with specific actions — and the launch team starts asking for your input instead of avoiding it.

If you're a Director / VP

Every failed product launch is a career risk. You coordinate across procurement, quality, marketing, and logistics — but risk visibility is fragmented. With Aversight, you see the entire launch risk surface in one place, updated daily.

If you're a CFO / CRO

A failed product launch costs €5–50M in write-offs, reputation damage, and recovery. Aversight catches the supply chain patterns, quality signals, and timeline risks that predict launch failures — weeks before they become write-offs.

Career impact, not just project impact

Supply chain analyst flagged a seasonal supplier reliability pattern that would have caused a stock-out during the holiday peak. Launch stayed on track. Got a 30% budget increase and a seat at the supply chain leadership table.

Supply Chain Analyst, global FMCG portfolio

Brand risk manager used AI recommendations to restructure the launch risk review process. Launch delays dropped by 45% across the portfolio. Promoted to Head of Portfolio Risk.

Brand Risk Manager, consumer goods brand

VP of Procurement used cross-supplier pattern intelligence to renegotiate 3 critical contracts. Saved €8M annually and reduced supply disruption risk by 60%.

VP Procurement, global consumer goods brand

Why your leadership will approve this

Your CFO wants:

Prevention, not firefighting. Aversight turns risk from a cost center into measurable savings — with data your CFO can put in the board deck.

Your CRO wants:

Competitive intelligence, not compliance overhead. Pattern recognition across the portfolio identifies opportunities, not just threats.

Without Aversight?

You stay stuck with manual spreadsheets, quarterly reports that arrive too late, and meetings where you present risks that executives politely ignore. The analyst stays invisible. The risk manager's assessments stay unread. The director keeps discovering supply chain failures at the moment of the stock-out, not 6 weeks before it.

Gets Smarter Over Time

Seasonal risk patterns, supplier reliability scores, launch delay predictors — all accumulated automatically. Your next product launch benefits from every previous one.

The average project overrun costs €2.3M. Calculate what earlier detection saves you →

Connects to Your Existing Stack

SAPPLM SystemsSupplier PortalsExcel

Read-only. No data migration. Your teams keep working as before.

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Your projects know more than you can see today.

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This dashboard is our demo lens. In production, scores and alerts live in your Power BI, your inbox, your workflows.

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