$900M–$1.8B SAM in complete whitespace — no competitor occupies organizational intelligence in government, and HP can reach every federal agency and all 50 states through existing procurement vehicles.
| Total HP deal value per agency | ~$15.6M over 3 years |
| Serviceable addressable market | $900M–$1.8B annually (federal + state) |
| Pilot to value | 90 days (X-Ray delivery in ~7–8 months total) |
SigmaEra AI analyzes meeting signals across an agency — thousands of meetings per week — to detect decision bottlenecks, coordination failures, and institutional knowledge loss that no existing tool surfaces. Government is the ideal vertical: 60–70% of senior leader time is in meetings, 30% of the federal workforce is retirement-eligible within five years, and $100B+ in inter-agency duplication savings remain unrealized. Only HP can deliver this — Sigma + HP IQ runs entirely on-device and on-prem within the ATO boundary (no FedRAMP needed), and existing procurement vehicles mean an agency can buy through the same contracts they already use for HP hardware.
| Federal Services Administration | |
|---|---|
| Profile | 15,000 employees, mid-size civilian agency (modeled on SSA/OPM/SBA) |
| Pilot outcome | $15–25M annualized customer value: $9.8M meeting time recovered, $1.6M FOIA savings, $5–20M knowledge-loss disruption avoided |
| HP deal value | $8.7M Year 1 (incl. hardware refresh) → ~$15.6M over 3 years |
| Key findings | Unblocked 11-month IT modernization stall by identifying 2 specific blockers across 6 oversight bodies; 3 of 14 inter-agency groups with overlapping scope; 40% of senior leadership meetings produced no decisions or clear action items; 2 retiring program directors mapped as irreplaceable network bridge nodes |
| Objection | Rebuttal |
|---|---|
| “Our data is too sensitive for AI.” | Sigma is on-prem, HP IQ processes on-device — data never leaves the endpoint or agency network; no cloud, no FedRAMP needed; air-gap is the core architecture, not a bolt-on. |
| “We already have M365 GCC.” | Viva Insights shows individual metrics (time in meetings, focus time); it cannot detect organizational decision patterns, coordination failures, or create searchable decision records across thousands of meetings — Sigma complements Teams GCC, it doesn’t replace it. |
| “No budget for another IT tool.” | Procure through existing SEWP V or GSA Schedule as an HP device extension — no new contract vehicle; 90-day pilot runs on existing HP hardware with minimal implementation cost. ROI demonstrated within the pilot window. TMF funding may apply. |
Who: Agency CIO / Deputy CIO (has IT budget authority, knows GSA Schedule/SEWP V/NASPO ValuePoint procurement vehicles, measured on FITARA scorecard)
Lead with: “What percentage of your senior leaders’ time goes to meetings vs. mission delivery? We can measure that in 90 days.”
Ask for: 90-day pilot scoped to one headquarters division (~3,000–5,000 employees), Teams GCC transcripts + calendar data, $150K–$300K
There is no direct competitor. No vendor offers meeting-signal-driven organizational intelligence with air-gapped deployment for government. Microsoft Viva is personal productivity, not organizational intelligence — and cannot deploy air-gapped. Palantir does mission data analytics on a different budget line. Generic transcription tools (Otter, Fireflies) have no FedRAMP, no air-gap, no org-level analysis. Every cloud-native competitor faces 12–18 months of FedRAMP plus 12–18 months to establish procurement vehicles. HP has a significant structural head start.
HP IQ’s on-device AI processes all meeting signals locally — PII filtering, summarization, signal preparation — before anything reaches the organizational intelligence layer. For CUI environments, initial processing happens inside the endpoint itself, within the ATO boundary by definition. No data leaves the device for cloud processing. No FedRAMP authorization applies. The HP Workforce Experience Platform gives the CIO a governance layer across all endpoints. The endpoint, the on-device AI model, and the platform are optimized to work together.