Pource
Texas data center project intelligence · Pource
Pource aggregates scattered permits, filings, property records, utility materials, and company statements into one evidence-backed record per Texas data center project. Like US Data Center Map, it reconciles fragmented public records to distinguish confirmed facts from announced claims, tracking what is actually being built rather than relying on self-reported capacity figures.
Why: Nearly identical approach but focused exclusively on Texas data centers. Same multi-source reconciliation wedge and evidence-based methodology. Geographic scope is narrower but depth appears comparable.
GridGlasses
U.S. power infrastructure build-out intelligence · GridGlasses / Gridwork LLC
GridGlasses resolves the U.S. power build-out into one graph by stitching together public records, connecting projects to the firms building them and public companies exposed. They capture point-in-time records from entirely public sources, creating a sourced, ranked dataset of grid infrastructure that tracks where work and capital are flowing.
Why: Broader infrastructure focus (entire grid build-out vs. just data centers) but identical transparency-layer wedge and public-record reconciliation method. Point-in-time capture ensures records aren't rewritten, similar lifecycle tracking philosophy.
Currence
Data center power project intelligence · Currence
Currence tracks 1,200+ planned U.S. data centers with project-by-project intelligence on power, equipment, participants, milestones, and costs. They score eight credibility factors per project, distinguishing announced capacity from buildable reality—serving equipment providers, utilities, and investors who need facility-level visibility into the AI-power buildout.
Why: Same data center infrastructure boom focus and credibility-scoring approach. Buyer profile (utilities, equipment providers, investors) closely matches. Less explicit about multi-source reconciliation methodology but credibility scoring implies similar validation.
Indax
Industrial facility and project intelligence · Indax
Indax maintains a live model of 2 million U.S. facilities built from permits, inspections, and filings, tracking new projects as they're filed and what runs inside every plant. They aggregate fragmented public records into facility-level intelligence for industrial OEMs and suppliers, though their scope extends beyond infrastructure to manufacturing facilities.
Why: Identical permit-based aggregation wedge but broader industrial scope (all facilities vs. data centers). Buyer profile differs—serves OEMs/suppliers rather than infrastructure planners. Same lifecycle tracking from filing through operation.
Basepoint
Energy infrastructure GIS intelligence · Basepoint
Basepoint aggregates 118 GIS layers and 155 live feeds from scattered public records and regulatory filings—queues, parcels, permits, and grid capacity from thousands of county sites, ISO portals, and federal databases. They clean, link, and maintain currency of energy infrastructure data that lives across fragmented government sources.
Why: Strong match on multi-source aggregation from fragmented government databases. Geographic enrichment (GIS layers) is core strength. Broader energy focus than data centers specifically, and live feeds suggest more real-time approach than monthly refresh.
GridIntel
Power project intelligence platform · GridIntel
GridIntel aggregates scattered public records—grid-operator queues, federal filings, state and county records, contracts, and company disclosures—to reveal who is really building each solar, wind, or battery project. They link fragmented pieces into complete project intelligence, recognizing that the truth about power projects exists in pieces across multiple sources.
Why: Nearly identical wedge (truth is public but scattered) and multi-source reconciliation method. Focus on renewable energy projects rather than data centers. Less emphasis on lifecycle completeness and grid-context enrichment than source company.
Manathric
Energy and AI infrastructure buildability intelligence · Manathric Intelligence
Manathric analyzes grid queues, sponsor history, physical constraints, and demand collisions to show where energy and AI infrastructure can actually be built. They serve infrastructure funds, data center developers, and energy teams by distinguishing real pipeline from 'ghost capacity' in grid queues, turning fragmented signals into decision-grade intelligence.
Why: Strong buyer profile match (infrastructure funds, data center developers) and similar credibility-filtering approach. More analytical/predictive (buildability assessment) than pure aggregation. Addresses same queue-vs-reality problem but with different methodology emphasis.
Physical Layer
Permit record aggregation platform · Physical Layer
Physical Layer normalizes 119 million permit records and 38 million license records from 1,104 sources into one schema, exposing construction market intelligence through web app, API, and warehouse feed. They aggregate fragmented municipal permit data into a unified record, though serving broader construction market rather than infrastructure-specific use cases.
Why: Identical permit-aggregation wedge and multi-source normalization. Massive scale (119M records, 1,104 sources) but serves general construction market rather than infrastructure planners. Less domain-specific enrichment (grid context, utility data).
CIPScout
Critical infrastructure project intelligence · CIPScout
CIPScout delivers decision-ready intelligence on critical infrastructure projects—from civil projects to data centers and energy grid expansion—before RFPs drop. They track the CIP lifecycle to help suppliers and contractors identify opportunities early, aggregating project signals across multiple infrastructure categories.
Why: Covers data centers within broader critical infrastructure scope. Lifecycle tracking is similar but buyer profile skews toward suppliers/contractors (pre-RFP intelligence) rather than infrastructure planners. Less detail on multi-source reconciliation methodology.
