AI Decision Intelligence Layer · Enterprise Execution

Stop tracking projects.
Start deciding portfolios.

AI-POS is the decision intelligence layer for enterprise PMOs. It reads your Jira, Microsoft Project, SAP and Excel, predicts execution risk weeks before it surfaces, and gives executives the recommendations they need — not another dashboard.

6–9 wks
earlier risk detection
70%
less manual reporting
faster executive decisions
<30 days
to first production insight
Built for execution-critical industries
Manufacturing
Banking
Energy
Telecommunications
Logistics
Enterprise IT
The enterprise execution gap

Your PMO is producing reports. Your portfolio is losing decisions.

Enterprises run hundreds of programs across thousands of dependencies. Every system tracks tasks. None of them tell leadership what to decide next.

Pain

Leadership sees problems too late

By the time a red status reaches the steering committee, the slippage is already in the quarter. PMO reports lag reality by weeks.

Pain

PMOs spend 40%+ of time reporting

Senior PMs and PMO analysts assemble decks instead of resolving execution risk. The work that creates value is the work no one has time for.

Pain

Risks are identified after the damage

Manual RAID logs and weekly status calls catch issues after they've already moved scope, cost or go-live dates.

Pain

No portfolio-level visibility

Executives see 200 projects as 200 status fields — not as one connected portfolio with dependencies, capacity limits and capital at risk.

The decision intelligence layer

One AI layer above the systems your enterprise already runs.

AI-POS does not replace Jira, MS Project, SAP or Excel. It sits on top of them — unifying signals, predicting outcomes, and recommending the next decision to your PMO and executive team.

  • Connects natively to Jira, Azure DevOps, MS Project, SAP S/4HANA, Salesforce, Outlook, Teams and Excel.
  • Normalizes 200+ project signals into a single execution graph across the portfolio.
  • Continuously scores delivery risk, dependency exposure and revenue at risk.
  • Generates board-ready briefings, reallocation plans and decision recommendations.
Live decision feed
● streaming
Risk · 92%just now
Atlas 2.0 — payments cutover slips Q3
Vendor capacity at 118%. Recommend pulling 2 FTE from Helios, defer Aurora UAT by 1 sprint. Revenue at risk: $4.2M.
Optimizejust now
Rebalance EMEA delivery cluster
Shifting 14% scope from Orion → Helix unlocks 22 capacity hours/wk, improves portfolio NPV by 7.8%.
Briefjust now
Board briefing ready · 1 page
12 programs · 3 escalations · 2 decisions required from COO before Friday.
Platform capabilities

Six AI capabilities. One execution layer.

Each module is built for enterprise scale — multi-tenant, SSO-ready, with auditable model outputs and human override at every recommendation.

Risk Intelligence

Predicts delivery slippage, budget overrun and scope drift 6–9 weeks ahead using cross-system execution signals.

Portfolio Optimization

Continuously rebalances scope, sequencing and investment across the portfolio to maximize NPV and strategic fit.

Executive Briefings

Generates one-page board and steering-committee briefings automatically — no slide assembly, no status chase.

Resource Intelligence

Detects allocation conflicts, vendor over-commitment and skill bottlenecks before they hit the critical path.

Decision Recommendations

Tells executives what to decide, with the trade-offs, dependencies and revenue impact already quantified.

Dependency Intelligence

Maps cross-program dependencies and shows the cascade impact of every delay, change or reallocation.

How it works

From data to decision in four steps.

A closed loop between your systems of record and your executive decision cadence.

01

Data

Connect Jira, MS Project, SAP, Excel, Teams and Outlook in days. No rip-and-replace, no new PM process.

02

Intelligence

Models score risk, dependencies, capacity and value across every project, every week, continuously.

03

Recommendations

AI proposes reallocations, sequencing changes and escalations with quantified trade-offs.

04

Decisions

PMO and executives approve, override or simulate alternatives — with full audit trail.

Outcomes

Measured in decisions, not dashboards.

Customers measure AI-POS by velocity of decisions and execution outcomes — not by feature adoption.

Faster executive decisions

Decision packages are pre-assembled with trade-offs and impact already computed.

6–9 wks
Earlier risk detection

Predictive models surface slippage long before status turns red.

70%
Less reporting effort

PMOs stop building decks. AI generates briefings, status and board narratives.

12–18%
Better portfolio execution

Continuous optimization improves on-time, on-scope and on-budget delivery.

Executive pilot

A 4–6 week pilot. One portfolio. One executive ROI report.

We deploy AI-POS against a slice of your real portfolio, connect to your real systems, and deliver a quantified ROI report you can take to the board.

Pilot scope
  • 10–30 active projects in one program or business unit
  • Connectors to Jira / MS Project / SAP / Excel
  • 1 executive sponsor, 1 PMO lead, 1 data SPOC
  • 4 to 6 calendar weeks, fixed scope
Expected outcomes
  • Predicted risks on 100% of in-scope projects
  • Quantified revenue and capacity at risk
  • Reallocation recommendations approved by sponsor
  • Reduced status / reporting effort, measured
Executive ROI report
  • Baseline vs. AI-POS delivery performance
  • Hours saved across PMO and program teams
  • Decisions accelerated, escalations avoided
  • Projected annualized portfolio impact
What you do not need
  • No data migration, no new PM tool
  • No process change for project managers
  • No long procurement — pilot SOW only
  • No production lift before ROI is proven
Enterprise outcomes

What execution leaders say.

Illustrative customer outcomes from regulated, multi-program enterprises.

Global manufacturer

"AI-POS flagged a tooling delay nine weeks before our program board would have. We protected a $14M launch window and re-sequenced two adjacent programs without overtime."

VP, Transformation Office · Tier-1 Industrial$14M launch protected
Tier-1 bank

"Our COO went from a 60-slide steering deck to a one-page AI-POS briefing. Decision cycle time on portfolio escalations dropped from 11 days to 3."

Head of Enterprise PMO · Global Bank3-day decision cycle
Telecom operator

"Resource Intelligence caught a vendor over-commitment our PMO had been arguing about for months. The recommendation saved a quarter of rework on the 5G core program."

Program Director · National Telecom1 quarter of rework avoided
Objections answered

The questions executives actually ask.

We already use Jira. Why do we need this?

Jira is a system of record for tasks. AI-POS is a decision layer over Jira and your other systems. It does not replace what your project managers do — it tells your executives what to decide based on what every system already knows.

We already have dashboards. How is this different?

Dashboards show you the past. AI-POS predicts the next 6–9 weeks of execution risk and recommends specific decisions: reallocate this team, defer that release, escalate this dependency. It is the layer above your dashboards, not another one.

Is AI replacing our project managers?

No. AI-POS removes the reporting work that consumes PMs and PMOs — status assembly, escalation prep, board decks. It gives your people back the time to actually resolve risk and lead delivery. Every recommendation is auditable and human-approved.

How long does deployment take?

First production insight in under 30 days. A full pilot in 4–6 weeks. Enterprise rollout is staged by business unit, with SSO, multi-tenant isolation and SOC 2-aligned controls from day one.

Decide before the quarter does

Bring decision intelligence to your portfolio.

Start with one program. Prove the ROI in 4–6 weeks. Roll out across the enterprise on the back of an executive ROI report — not a vendor pitch.