Because infrastructure decisions don't just affect balance sheets — they affect communities, grids, and the world that runs on them.

Infrastructure decisions that operators can actually defend.

InfraMind helps data center operators, infrastructure owners, and capital allocators reduce energy cost, water impact, constraint risk, and decision lag — with deterministic scoring built for energy-constrained, capital-intensive environments.

REQUEST A DEMO See how it works
4.4→12%
U.S. data center share of total electricity consumption — 4.4% in 2023, projected to reach 6.7–12% by 2028. The grid wasn't built for this. Source: DOE / Lawrence Berkeley National Laboratory, 2024
100%
Deterministic scoring — scores are aggregated at the decision layer, not the model layer. Every output is auditable, explainable, and defensible.
PLL-19
Georgia Power's Power and Light Large tariff (PLL-19) — a multi-component bill structure including demand ratchet provisions, fuel cost recovery, environmental compliance and demand side management schedules, and a municipal franchise fee that most energy platforms don't fully model. InfraMind is being built to model every component. The same depth is planned for additional utility tariffs and ISO markets.
ISO +
Designed for both ISO and non-ISO energy market complexity
Why Now

AI demand is rising faster than infrastructure planning can keep up.

Operators are being asked to make larger energy, capacity, and capital decisions under tighter timelines. The cost of waiting, guessing, or relying on black-box outputs keeps getting higher.

01 — DEMAND

Power demand is accelerating

AI workloads are increasing energy intensity across modern infrastructure, which raises the stakes on every siting, procurement, and operating decision.

02 — TIMING

Decision windows are shrinking

Tariff exposure, capacity constraints, and demand-response opportunities move faster than spreadsheet-based analysis can support.

03 — TRUST

Boards still need defensible logic

High-stakes infrastructure teams cannot act on recommendations they cannot audit. Explainability is a requirement, not a feature.

04 — WATER

Water pressure is the next constraint

Data centers consume millions of gallons annually. Watershed stress, drought conditions, and interstate water rights disputes are active risk factors — invisible to platforms that only model energy.

The Problem

Infrastructure decisions are too consequential to make on gut instinct.

Energy-constrained infrastructure operators face compounding pressure — rising demand, tariff complexity, water stewardship risk, and capital allocation decisions with 10-year consequences. Most teams are still making those calls with spreadsheets, static dashboards, and tribal knowledge. InfraMind is built to help teams move faster with recommendations they can explain to operators, executives, and investment committees.

01 — ENERGY

Tariff complexity is only getting harder

PLL-19, demand response windows, ISO market exposure — the variables multiply faster than any team can manually model.

02 — CAPITAL

Capital allocators need decisions they can defend

CFOs and investment committees don't want a recommendation — they want to see the reasoning, the constraints, and the confidence level behind it.

03 — CAPACITY

Capacity planning can't wait on manual analysis

When demand signals shift, the window to act is narrow. Slow analysis means missed optimization and stranded capital.

04 — TRUST

Black-box AI doesn't work in boardrooms

Operators need to understand and explain every recommendation. If you can't audit it, you can't act on it at scale.

05 — WATER

Water risk starts at site selection, not operations

A data center can pass every energy and land check and still be built on a stressed watershed or inside an active water rights dispute. By the time you're operational, it's too late to fix a bad watershed decision.

06 — COMMUNITY

Infrastructure impact doesn't stop at the fence line

Energy draw, water consumption, and grid stress ripple into surrounding communities and ratepayers. Operators who can quantify and manage that impact are better positioned with regulators, partners, and the public.

How It Works

Deterministic scoring. LLM narrative. Full auditability.

InfraMind separates the decision logic from the language layer — so every recommendation is grounded in verifiable data, not inference.

STEP 01

Ingest & Validate

Energy pricing, site constraints, tariff structures, and water stewardship signals are designed to be ingested, validated, and structured through a validated data pipeline — planned coverage includes CAISO, PJM, ERCOT, Georgia Power PLL-19, EIA, EPA eGRID, USGS watershed data, WRI Aqueduct, and NOAA Drought Monitor, with additional markets to follow.

STEP 02

Score & Constrain

A 12-layer constraint stack is designed to run deterministic scoring against your infrastructure parameters — with PLL-19 ratchet logic, conflict detection, and bounds-checking.

STEP 03

Recommend & Audit

Outputs are surfaced as explainable, auditable recommendations — with LLM narrative labeled separately so operators always know what is scored logic and what is generated language.

Operator Dashboard
Illustrative demo data shown for product visualization.
InfraMind · Operator Dashboard · Illustrative · Colo ATL-01 · Georgia Power PLL-19
ILLUSTRATIVE ●
CURRENT LMP
$42.18
ISO reference · /MWh
PLL-19 RATCHET
87.4%
▲ Watch window active
LOAD
22.4MW
87% utilization
PROJECTED SAVINGS
$187K
P50 · this month
ACCURACY — MTD
94.2%
MAPE within bounds
ISO MARKET REFERENCE · 24-HR · ILLUSTRATIVE
CAISO
PJM
ERCOT
PEAK WINDOW (EXAMPLE) PLL-19 RATCHET THRESHOLD
00:00
06:00
12:00
14:00–20:00
NOW
P2 · PROBABILISTIC FORECAST
P10 — conservative
$142K
P50 — base case
$187K
P90 — optimistic
$231K
P10 $142KP90 $231K
CONFIDENCE: HIGH
Constraint checks · PASSED
RECOMMENDATIONS · P3 DECISION ENGINE
3 ACTIVE
ENGINE: DETERMINISTIC · LLM: EXPLANATION ONLY
1
Shift batch workloads to off-peak window
LOW RISK HIGH CONFIDENCE OVERNIGHT BATCH
$187K
P50 SAVINGS / MONTH
P10 $142KP90 $231K
Move 4.2 MW of non-critical batch compute out of the 6pm–9pm window to 11pm–5am. Lowers the month's highest 30-minute demand, which sets PLL-19 billing demand and the summer ratchet floor.
Execution: Coordinate with ops team. No SLA exposure. Pre-approved window.
Demand Δ: -$8.4K
Carbon Δ: -12.4 tCO₂e
APPROVE ACTION →
2
Cap peak demand at 19.8 MW for 3 hours
MED RISK HIGH CONFIDENCE DEMAND CAP
$94K
P50 SAVINGS / MONTH
P10 $71KP90 $118K
3
Curtail cooling load · Building C · Peak window
SUPPRESSED · Thermal floor constraint — never silently altered
$61K
not actioned
WHY? → Ambient temp 94°F exceeds thermal floor threshold. Re-evaluates at 88°F.
LLM NARRATIVE · EXPLANATORY ONLY
Shifting 4.2 MW of batch workloads to the 11pm–5am window lowers the month's highest 30-minute demand, which reduces PLL-19 billing demand and ratchet exposure. The $187K P50 figure is an illustrative output of the probabilistic forecast. Recommendation #3 was suppressed — thermal floor constraints in Building C prevent safe curtailment under current 94°F ambient conditions.
Scoring engine output is authoritative. This narrative is explanation only and does not alter any scored dimension.
SCOPE 2 CARBON INTENSITY
817.4
lbs CO₂/MWh · SRSO subregion
Source: EPA eGRID
CARBON SAVED — MTD
47.3t
CO₂e avoided this month
DEMAND RESPONSE REVENUE
$18.4K
captured MTD (example)
DR EVENT EXAMPLE · Opt-in by 2:30pm
COMMUNITY RATEPAYER IMPACT
In development
planned P4 module
InfraMind is being built to help operators and regulators understand how large-load decisions affect ratepayers. Quantification methods are in development.
P4 · Water Impact Module
WUE BASELINE 1.9 L/kWh · USGS HUC-8 · ILLUSTRATIVE
WATER USAGE EFFECTIVENESS
1.42 L/kWh
current · 30-day rolling avg
vs baseline 1.9↓ 25.3%
Illustrative modeled view: WUE is estimated from IT load and ambient conditions.
WATER AVOIDED — MTD
2.1M gal
vs unoptimized baseline · this month
Source: modeled from IT load and ambient conditions.
WATERSHED STRESS · HUC-8
LOW
Chattahoochee · USGS gauge 02335000
7-day flow index 84th pct
Drought monitor D0 — Abnormally Dry
Stress flag CLEAR
WATER RISK ADVISORY
NO ACTIVE WATER FLAGS
Monitored conditions include cooling tower blowdown, recirculation rate, and seasonal evaporative loss — within normal bounds in this example.
PROJECTED 90-DAY
6.3M gal avoided
illustrative · modeled
INFRAMIND · ILLUSTRATIVE INTERFACE · NOT LIVE DATA
SERC TERRITORY · GEORGIA POWER PLL-19 · SCHEDULE EFFECTIVE JUNE 2026
Site Intelligence

Every site. Every decision. One dashboard.

InfraMind is being built to surface everything that matters about your infrastructure in one place — so operators and capital allocators can evaluate performance and make smarter decisions about where to build, expand, and invest next. Six scoring dimensions including Water Stewardship mean risk is caught at site selection, not after capital is committed.

VISIBILITY

Portfolio-wide site awareness

Energy consumption, capacity utilization, and constraint status — designed to be surfaced across every site in your portfolio.

INTELLIGENCE

Decision-ready insights

Scored recommendations tied directly to your site data — enabling teams to evaluate not just how sites are performing, but where future capacity, expansion, and capital should be deployed.

TRANSPARENCY

Boardroom-ready reporting

Every insight is auditable and explainable. When leadership asks why — operators have an answer, not a black box.

Site Intelligence Dashboard
Illustrative portfolio data shown for product visualization.
InfraMind · Site Intelligence · Illustrative Portfolio View
FUND BUYER VIEW
ENGAGEMENT
Piedmont Georgia Portfolio — Site Selection
FACILITY SIZE
96 MW
SITES ANALYZED
4
MARKET
Georgia · Non-ISO
ACTIVE
SCORING
ECONOMICS
NARRATIVE
TOP SITE
ATL-1
composite 89/100
PORTFOLIO SAVINGS
$1.8M
annualized P50
AVG CARBON
817
lbs/MWh · SRSO eGRID
ACTIVE FLAGS
1
Ratchet exposure watch · ATL-1
SITE SCORING — 6 DIMENSIONS · DETERMINISTIC
SITE
GRID
LAND
ENERGY
REG.
COMM.
WATER
SCORE
ATL-1
Metro Atlanta · 96MW
92
85
87
91
88
84
88
SUW-1
North Metro · 72MW
84
88
82
86
79
81
83
AUG-1
East Georgia · 68MW
⚑ WATER FLAG
79
91
88
83
82
71
82
FAY-1
South Metro · 48MW
⚑ HIGH WATER RISK
81
77
84
80
76
58
76
WATER STEWARDSHIP · DATA SOURCES
USGS NWIS streamflow · WRI Aqueduct watershed risk · NOAA/USDA Drought Monitor · EPA WATERS 303(d) impairment · Georgia tri-state water rights litigation status
SITE SCORE · ATL-1 · 6 DIMENSIONS
GRID ACCESS LAND ENERGY REG. RISK COMMUNITY WATER 89 /100
Grid Access 92
Land 85
Energy Econ 87
Reg. Risk 91
Community 88
Water Stew. 84
ESG + COMMUNITY IMPACT · ATL-1
SCOPE 2 EMISSIONS
312K
tCO₂e · annualized · illustrative
GRID STRESS
MED
SOCO · current
COMMUNITY RISK
LOW
EJScreen · ATL-1
ANNUAL CARBON @ $50/t
$15.6M
illustrative exposure
WATERSHED STRESS
LOW
Chattahoochee · D0
WUE SCORE
84
USGS · WRI Aqueduct
CAPITAL ALLOCATOR SUMMARY
Portfolio IRR impactmodeled per engagement
20-year OpEx reduction$36M
Constraint risk flag1 site
Audit trailCOMPLETE
ECONOMICS TAB — 20-YEAR ENERGY MODEL · ATL-1
20-YEAR ENERGY ECONOMICS
BASELINE COST (20yr)$1,143.7M
WITH INFRAMIND OPT.$1,107.7M
20-YEAR SAVINGS$36M
ANNUAL AVG SAVINGS$1.8M / yr
LEVELIZED COST (20yr)$0.068/kWh
ASSUMPTIONS96 MW · full load · flat $0.068/kWh
RATE FREEZE WINDOWThrough 2028
INFRAMIND P5 → P1–P4 FLYWHEEL
A site selected with P5 and operated with InfraMind from Day 1 captures the full $36M in 20-year optimization savings immediately. The figure assumes P1–P4 active from first month of operation.
CARBON COST EXPOSURE SCENARIOS · ANNUAL
Illustrative annual exposure if emissions were priced. Assumes a 96 MW facility at full load and 817.4 lbs CO₂/MWh (SRSO subregion).
Low ($25/ton)$7.8M
Moderate ($50/ton)$15.6M
High ($100/ton)$31.2M
Severe ($200/ton)$62.4M
Scenario values are illustrative and scale linearly with the carbon price assumption.
NARRATIVE TAB — SITE RECOMMENDATION · ATL-1
SITE RECOMMENDATION NARRATIVE — ATL-1
Generated narrative · illustrative scenario · EXPLANATORY ONLY
✓ ENGINE VERIFIED
ATL-1 ranks first among the four Georgia candidate sites with a composite score of 89/100, driven by strong grid access — substantial available capacity and a short estimated interconnect timeline in this illustrative scenario — and favorable energy economics under Georgia Power's tariff structure. The PSC rate freeze through 2028 locks in current base rates during the critical first years of operation, reducing long-term energy cost uncertainty. Community risk is assessed as LOW in this illustrative scenario, with no active environmental justice flags. The primary risk flag is demand ratchet exposure during the first summer peak window — manageable with InfraMind P1–P4 demand management active from Day 1.
LLM explanation aligns with the top-ranked site (ATL-1, composite 89/100). Consistency check: PASSED. Scoring engine output is authoritative — this narrative is explanation only and does not alter or override any scored dimension.
EXECUTIVE SUMMARY — SUITABLE FOR PITCH DECK
InfraMind analysis of 4 Southeast candidate sites for a 96 MW data center identifies ATL-1 (Metro Atlanta) as the optimal development location. The site achieves a composite score of 89/100, driven by strong grid access and a 20-year levelized energy cost of $0.068/kWh. With InfraMind P1–P4 optimization active from Day 1, estimated 20-year energy savings are $36M. The Georgia Power rate freeze through 2028 provides cost certainty during the critical early operating window.
INFRAMIND P5 · SIX-DIMENSION SCORING · LLM EXPLANATION ONLY — SCORING IS DETERMINISTIC
DATA: FERC FORM 727 · CENSUS TIGER · FEMA NFHL · EPA EJSCREEN · NCSL · USGS NWIS · WRI AQUEDUCT · NOAA/USDA DROUGHT MONITOR · EPA WATERS · GEORGIA POWER FILED TARIFFS

Built for operators making high-stakes infrastructure decisions.

InfraMind is an Atlanta-based decision intelligence company founded in 2026. We're building the platform we always needed — one that treats infrastructure decisions with the rigor and transparency they deserve.

The stakes aren't just financial. AI-driven demand is accelerating energy consumption and water use at data centers faster than the grid and watersheds were built to handle — and those pressures don't stay inside the fence line. They ripple into communities, utilities, and the environment. Better infrastructure decisions aren't just good for operators. They're good for everyone downstream.

Tiauna Paul
FOUNDER & CEO · INFRAMIND SYSTEMS LLC

Infrastructure operators are making billion-dollar decisions — where to build, how to manage energy cost, how to allocate capital across a portfolio — with tools that were never designed for the complexity they're navigating today.

InfraMind was founded to change that. Not to build another dashboard, but to build the decision intelligence layer that this industry has never had — deterministic, auditable, and built for the operators who can't afford to be wrong.

The platform starts where the complexity is highest. In Georgia, that means modeling the full Georgia Power PLL-19 tariff structure — the fuel cost recovery rider, environmental compliance cost recovery (ECCR), demand side management, ratchet clause exposure, and municipal franchise fee that collectively govern what large commercial and industrial customers actually pay. The same depth and rigor is the goal wherever InfraMind operates.

Every output is explainable. Every recommendation has a source. Water stewardship is scored at site selection, not after capital is committed. Nothing is a black box — because in this industry, it can't be.

InfraMind is built in Atlanta, incorporated in Georgia, and designed from the ground up for energy-intensive infrastructure operators who need to defend every decision they make.

Get in Touch

See InfraMind in action.

Operator demos begin early 2027. We're selecting our pilot cohort now. If you're a data center operator, infrastructure owner, or strategic partner managing energy cost, capacity risk, tariff complexity, or capital allocation decisions at scale, request your spot. Selected operators will be contacted directly.

Or email directly: pilot@inframindsystems.com