From analyst dashboard to boardroom report — Aversight connects to your existing systems, thinks about your data, and delivers intelligence where your team already works.
Aversight sits between your existing data and your existing tools. No new interface to adopt. No migration required. Just intelligence, delivered where decisions happen.
0–100 composite score, 5 dimensions, updated daily
Automated alert identification across all connected sources
Cross-project intelligence from your portfolio history
Actionable guidance: who, when, and expected impact
What-if simulation and Monte Carlo probability models
AI-written executive summaries and status reports
Accumulated patterns, decisions, outcomes — grows smarter with every project cycle
Native visual layer inside your existing workspace — optional, not required
AI-written PDFs delivered to inbox on schedule
Risk escalations pushed to the right stakeholder at the right time
Alerts and summaries in channels your team already uses
Machine-readable output for downstream automation
Optional: push recommendations back into source systems
Generated outputs become new training signals — the system learns from every decision made on its recommendations.
Most platforms say “AI-powered” and leave it at that. Aversight uses three distinct approaches — each serving a different purpose, each fully transparent.
Layer 1 — Deterministic
Rules Engine
Configurable scoring weights, thresholds, and alert triggers. Every score is explainable. Every alert is traceable. Every rule is auditable.
Layer 2 — Heuristic
Pattern Engine (ML)
Statistical pattern recognition across your entire portfolio history. Detects anomalies, correlations, and escalation signals that no human could see across 50+ projects.
Layer 3 — Generative
LLM Recommendations
Claude, GPT-4o, or Llama — model-agnostic. Takes the outputs of Rules + Patterns and generates human-readable recommendations, reports, and executive summaries.
All three layers feed on accumulated generated data — scores, trends, patterns, recommendations. Each cycle makes the next one smarter. The rules stay transparent. The patterns get sharper. The recommendations get more specific.
Each module operates independently and in combination. Together they form a reasoning layer that no single BI tool or add-on can replicate.
Every project receives a composite 0–100 risk score updated daily. Five configurable dimensions: schedule, budget, resource, dependency, and strategic alignment. Drill down to any driver.
5 dimensions · Daily refreshAutomated anomaly detection runs continuously across all connected sources. Threshold breaches, velocity drops, spend deviation, and cross-project contagion signals surface without any manual monitoring.
Continuous monitoringAversight matches current project signals against historical patterns in your portfolio. “85% of projects with this constellation escalated within 6 weeks” — that insight only exists because data was accumulated.
Cross-project intelligenceNot just what is wrong — but what to do about it. Recommendations include the responsible owner, the optimal intervention window, and the estimated impact of action versus inaction.
Who, when, impactWhat-if modeling with configurable drivers. Monte Carlo simulation generates probability distributions for budget, timeline, and resource outcomes. Best, mid, and worst case in seconds, not days.
Monte Carlo simulationAI-written executive summaries and full status reports, formatted to your standard. What takes a PMO four hours of data gathering and writing takes Aversight twenty minutes, end to end.
20 min vs. 4 hoursFor evaluators who want to see the mechanics, not just read the labels. Six engine modules, each with real output and the exact data that drives it.
Every project gets a composite score once per 24 hours. Five deterministic signals feed a transparent weighted sum. The score is not a black box — every component is surfaced and every weight is editable.
Rules fire when defined thresholds break. Patterns fire when your current project starts matching a historical overrun signature. Both are logged with evidence and retrievable for audit.
Each active project is embedded into a 248-feature vector and ranked against your completed projects. When the closest matches overran, you get warned. When a match was flagged false, the engine downweights that signature next time.
Claude turns the deterministic rule output and ML pattern match into a plain-language action. It uses only data the engine has already verified. No hallucination layer. Every prompt and output is audit-logged.
Before your morning meeting, Aversight runs 1,000+ Monte Carlo simulations per active project. You get P5 / P50 / P95 score distributions and a ranked list of the drivers that move the outcome most.
PMOs lose 4 hours every Friday aggregating status. Aversight ships the same output as a weekly brief, generated from live data at 07:00 Monday morning — with every claim cross-linked to the underlying evidence.
Unlike a dashboard that shows the same data forever, Aversight accumulates context. Each project cycle adds to a growing institutional knowledge base that makes every subsequent analysis more precise.
Scores generated from raw data as-is. Immediate signal from existing sources.
Direction matters. Scores trend against prior readings. Early drift becomes visible.
Recurring patterns emerge across projects. Correlations that no spreadsheet would surface.
Historical outcomes train forward-looking models. “This pattern led to overrun” becomes a live warning.
Your organisation’s full decision history. Every alert, recommendation, outcome. A living knowledge base no new hire can replicate.
Generated intelligence — new data that didn’t exist before
Risk Scores
daily, per project
Alerts
pattern-triggered
Trends
week-over-week
Patterns
cross-project ML
Recommendations
LLM-generated
Reports
weekly intelligence
Every item above feeds back as input to the next scoring cycle. Your knowledge base grows with every analysis — automatically, irreversibly.
The moat. Not lock-in — but irreplaceable accumulated intelligence. Switch off Aversight and the data stays yours. The compounding intelligence does not.
No data migration. No new fields to fill in. No workflow changes. Aversight operates like a silent observer — reading everything, writing nothing, never interrupting how your teams work.
Output is pluggable: Power BI today, Slack tomorrow, Jira tickets next month. The engine stays the same — only the delivery channel changes.
Project milestones, budgets, resource allocations, procurement data
Task dependencies, timelines, resource assignments, critical path
Documents, status updates, meeting notes, risk registers
Legacy data, manual registers, budget trackers, custom reports
Existing data models, calculated measures, transformed datasets
Sprint data, issue tracking, velocity metrics, backlog health
Pipeline status, work items, deployment frequency, code changes
Incident data, change requests, SLA compliance, service health
Power BI is an excellent visualisation tool. Aversight is not a visualisation tool. The question is not which one to choose — it is understanding what each one actually does.
| Capability | Power BI | Aversight |
|---|---|---|
| Visualises historical data in charts and reports | Yes | Yes |
| Cross-source intelligence synthesis | No | Yes |
| Automated pattern recognition across projects | No | Yes |
| Anomaly detection without manual thresholds | Basic | Yes |
| Contextual AI recommendations with owner + timing | No | Yes |
| Learns from outcomes over time | No | Yes |
| Builds institutional memory of decisions and outcomes | No | Yes |
| Generates AI-written reports automatically | No | Yes |
All four options deliver the same intelligence layer. On-premise is preferred for regulated industries where data sovereignty is non-negotiable.
Deploy Aversight entirely within your own data center. No data leaves your network perimeter at any point. Full control over updates, access, and retention. The default choice for pharma, energy, financial services, and defence-adjacent programmes.
Azure data centers with configurable region selection. Production-grade security. Seamless integration with existing Microsoft 365 and Azure AD environments.
AWS infrastructure across global availability zones. Scalable compute for large portfolios with hundreds of concurrent projects and data sources.
GCP with native BigQuery integration. Suited for organisations already operating within the Google Cloud ecosystem or requiring advanced analytics pipelines.
Enterprise security is not a feature. It is the baseline. Aversight is designed for environments where data governance, auditability, and regulatory compliance are non-negotiable.
Annual independent audit of security, availability, and confidentiality controls
Information security management system, certified and maintained
GDPR, CCPA, and HIPAA frameworks supported across all deployment modes
Transparent, auditable, human-in-the-loop. Aversight is designed for EU AI Act compliance from the ground up — explainable scoring, full audit trail, no autonomous decisions without oversight.
Identity provider integration with enterprise SSO and SAML 2.0 support
AES-256 at rest, TLS 1.3 in transit. No plaintext data at any layer.
Complete tamper-evident activity trail for every query, recommendation, and configuration change
No. Aversight is a middleware intelligence layer, not a visualisation replacement. It connects to your existing systems and can deliver its outputs directly into Power BI, Teams, email, or any channel you already use. Your dashboards stay. They just become more intelligent. This dashboard is our demo lens. In production, the intelligence runs underneath your existing tools.
No migration required. Aversight connects read-only to your existing systems via secure connectors. Your data stays exactly where it is — in SAP, SharePoint, Jira, or wherever it currently lives. We never write to your source systems unless you explicitly enable optional writeback.
Every project cycle generates structured data: risk scores, alerts raised, recommendations made, and — critically — what happened next. Did the escalation occur? Did the budget overrun? Was the recommendation acted on? Aversight logs outcomes and uses them to continuously refine its pattern models. After six months, the system understands your organisation’s specific risk signatures in a way no out-of-the-box tool can approximate.
Your source data always remains in your systems — we never move or own it. All structured intelligence generated by Aversight (scores, patterns, recommendations, audit logs) is fully exportable in standard formats. You leave with everything Aversight built. The compounding forward-looking intelligence, however, stops accumulating the moment the system is switched off.
Yes. Aversight is model-agnostic at the LLM layer. We support GPT-4o, Claude, Llama, Mistral, and custom fine-tuned models. On-premise deployments can run entirely on local models with no external API calls. You choose the model stack that fits your data governance requirements.
Connector setup and initial configuration typically takes two to three weeks. First scored outputs are visible within the first week. Full pattern-recognition capability develops over the first two to three months as the knowledge base builds. On-premise deployment adds approximately one week for infrastructure provisioning.
We map your current systems, identify the highest-value connectors, and show you first outputs in under three weeks.
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