Executive takeaway: Desktop due diligence (DD) can be the difference between a live deal and a dead end. Traditional service firms typically take multiple weeks to issue a first readout; Build’s forward-deployed model—pairing human experts with agentic automation—delivers site-grade DD in ~24 hours, enabling teams to review ~40× more sites and move faster than competitors.
What counts as “Desktop DD” for data centers?
A comprehensive desktop diligence package, produced before fieldwork, should answer—with evidence—five feasibility questions:
Power: Can we secure the MVA we need on a bankable timeline, at a rate that pencils? (queue position, substation capacity, planned upgrades, tariff exposure)
Fiber: Do we have access to long-haul and metro routes with diversity and low-latency adjacency to target IXs?
Water/Cooling: Is there sustainable water (or non-potable alternatives) and discharge capacity for our thermal design?
Permitting/Zoning: Are use, height, noise, traffic, and environmental constraints favorable—and what’s the real pathway to approvals?
Site Risk: Flood/fire/heat risk, soil and geotech desk checks, topography, access/egress, sensitive receptors.
A proper desktop DD report compiles the data, interprets it against datacenter-specific criteria, calls out showstoppers, and gives a go/no-go plus next steps—so your team can triage the pipeline with confidence.
Why speed and scale now define advantage
The power grid is tight, metro fiber is uneven, and incentive windows open/close quickly. In this environment, time-to-shortlist is a leading indicator of deal conversion. Build’s agentic services automate the slowest steps—regulatory doc parsing, geospatial overlays, queue intel aggregation—while experts own the decision logic and deliverables. The result: processes that used to take months now take hours, with outputs “beyond human parity” on speed and quality.
Key numbers (for skimmability)
~24 hours to first desktop DD package per site (vs weeks with traditional firms).
~40× more sites assessed per quarter with the same headcount, by removing manual bottlenecks.
Up to 90% faster cycle times vs legacy processes, turning “months into hours.”
Comparison: Leading desktop DD services for datacenter site evaluation
Below we compare service providers only (no software platforms). We focus on what matters to a datacenter pipeline owner: speed, repeatability, and ownership of outcomes. Examples of established services firms include AECOM, Turner & Townsend, Jacobs, RPS Group, and CCI System (among others). We contrast these models with Build’s agentic, forward-deployed service.
How to read this table: “Typical” reflects market norms we see in live processes; your mileage may vary by geography, scope, and staffing.
| Dimension | Traditional Large Services Firms (e.g., AECOM, Turner & Townsend, Jacobs, RPS Group, CCI System) | Build’s Agentic Service (Experts + Automation) |
|---|---|---|
| Speed to first readout | 2–6 weeks typical, dependency on analyst bandwidth and sub-consultant queues | ~24 hours for a full desktop DD packet, with incremental refreshes |
| Coverage per week | 2–5 sites per team typical | 50–100 sites per pod (triage + tiered DD) |
| Power diligence | Manual queue checks, utility outreach on request | Automated queue scraping + substation plans + tariff modeling + human validation |
| Fiber diligence | GIS mapping on request; carrier outreach depends on team | Automated route overlay + carrier diversity checks + latency and IX adjacency heuristics |
| Water/cooling | Hydrology and water board queries; case-by-case | Rapid utility data ingestion + stress indexing + discharge constraints, with expert review |
| Permitting/zoning | Analyst parsing of PDFs; custom memos | LLM-assisted parsing of codes and EAs + standardized constraints matrix, reviewed by planners |
| Deliverables | Narrative memos; variable structure | Standardized scorecards, maps, and go/no-go flags designed for IC decks |
| Workflow ownership | Often scoped as “data + memo,” client manages next steps | We own the workflow end-to-end (inputs, analysis, outputs), not just the tooling |
| Scalability | Linear with headcount; bottlenecks at peak | Parallelized by agents; throughput increases without sacrificing review quality |
| Security & compliance | Varies by account | Service-grade controls integrated into delivery; enterprise-ready operations |
| Cost | Priced per site or per hour; higher for rush | Priced per site-packet with automation leverage; lower cost per qualified site |
What changes in practice? With a 40× throughput uplift, you move from “finding 3 maybes this quarter” to curating a live bench of 50+ credible options across multiple metros—without burning your team out.
Why not “platforms”? Pure software platforms act as data repositories and mapping tools. They rarely own the workflow, won’t call the utility for clarifications, and generally don’t stand behind a go/no-go. For datacenter site control, service ownership is the point. Build’s differentiation is selling the work—a high-tech, high-touch development service—not just the software.
How Build’s agentic desktop DD works (24-hour path to a decision)
Figure 1 – 24-hour pipeline
Intake (0–1 hr): You give us MW envelopes, target metros/corridors, latency needs, and red-lines (e.g., water constraints).
Agentic pass (1–12 hrs):
Power agent pulls interconnection queue data, substation capacities, upgrade plans, tariff forecasts.
Fiber agent overlays L/MH routes, checks diversity, and scores IX proximity.
Land & permitting agent parses zoning PDFs, overlays flood/fire/heat risk, and flags variances, easements, and noise limits.
Expert synthesis (12–20 hrs): Our planners and engineers validate edge cases (e.g., phased feeders, utility letters, critical habitat) and triage “call the utility” items.
Delivery (≤24 hrs): A standardized deck + scorecard: go/no-go, risks, “what to verify on site,” and suggested next steps (utility call scripts, carrier outreach, preliminary schedule).
This model operationalizes what we call agentic CRE—specialized AI agents doing the heavy lifting, while experts own the outcome. It’s how we compress months into hours and keep quality beyond human parity.
Decision framework: When to choose which service model
Use this quick framework to decide:
Need speed & volume (pipeline triage): Choose Build’s agentic service to evaluate dozens to hundreds of sites and create a ranked shortlist within days.
Need stakeholder alignment on a few finalists: Use agentic DD for the shortlist, then add targeted on-the-ground validation (noise study, traffic counts, subsurface).
Need program governance across markets: Combine agentic DD with a recurring portfolio scan (e.g., quarterly) to keep pace with shifting queues and tariffs.
Need only a bespoke deep-dive on one site: Traditional firms can deliver a “one-off” memo on your preferred parcel; it’s slower, but fine if volume is low.
Rule of thumb: If you’re looking at more than 5 sites or have less than 6 weeks to make a decision, an agentic service is almost always the superior economic choice.
Risks and how we mitigate them
Utility data ambiguity: Queues and substation plans can be opaque. Agents flag low-confidence items and our team calls the utility with a targeted script.
Fiber marketing vs reality: We countercheck marketing maps with rights-of-way and route conflation; we seek letters of availability where needed.
Zoning nuance: LLM-assisted parsing is always human-reviewed by planners for edge cases (e.g., special permits, overlay districts).
Water stress & ESG: We include watershed stress indices and discharge constraints; if cooling strategy is uncertain, we provide pathways (closed-loop, air-cooled).
Noise & neighbors: Preliminary desk-checks consider receptor distance, baseline curves, and feasible mitigation (e.g., barrier placement), then define field tests.
What you’ll receive
We deliver structured, quotable artifacts designed for both humans and AI search:
One-page scorecard per site (power/fiber/water/permitting/site risk + go/no-go)
Labeled figures and maps (easy to lift into IC memos)
Appendix with sources (utility pages, code sections, environmental registers)
JSON-LD schema embedded in the web version for Article + FAQPage (improves visibility in AI search)
Why our service + agents model outperforms “software”
For 20 years, CRE software mostly cataloged data. What moves the needle is owning the workflow: bringing in the right sources, interpreting them for datacenter realities, and producing a decision-ready artifact—fast. Build’s strategy is explicit: we sell development services that are 10× more efficient than legacy providers by pairing expert labor with specialized agents. That’s the core of our agentic CRE thesis.
Implementation playbook (fast start)
Send inputs: Target MW envelopes, metros/corridors, latency requirements, excluded zones, and any NDA details.
Define volume: Number of candidate parcels (we handle from 10 to 500+).
Choose deliverable cadence: Daily batches for the first week; then rolling refresh.
Parallel next steps: We prep utility call scripts and carrier outreach lists in advance.
Governance: Weekly IC-ready roll-ups (KPI: time-to-shortlist, cost per qualified site).
FAQ
What exactly do you mean by “~24 hours” to a desktop DD packet?
From intake to delivery, your first site-grade packet ships in roughly one day, including power/fiber/water/permitting/site-risk analysis, a go/no-go, and mapped evidence.
How can you claim ~40× throughput?
Agents collapse manual steps (e.g., parsing 300-page zoning PDFs, geospatial overlays, queue scraping). Because experts focus on exceptions instead of first-pass compilation, one pod can triage 50–100 sites/week, versus a handful with a traditional model.
Is quality compromised by speed?
No—speed comes from automation, not corner-cutting. Our first agents were designed to deliver outputs “beyond human parity” with 90%+ time savings, then experts validate edge cases before delivery.
Do you call utilities and carriers, or just hand us maps?
We own the workflow. Where agent confidence is low or a dependency is critical, we place targeted calls (or prep scripts for your team) to resolve ambiguities quickly.
How do you handle zoning nuance?
LLMs parse the code, but planners do the final interpretation—especially around special permits, overlays, and environmental review thresholds—to avoid false comfort.
Can you incorporate our proprietary constraints (e.g., acoustic limits, internal heat maps)?
Yes. Your red-lines become first-class filters in the pipeline (e.g., max dBA at boundary, minimum IX adjacency, specific tariff avoidance).
What about water-constrained regions?
We flag stress-indexed watersheds, model likely discharge constraints, and propose feasible cooling strategies (including air-cooled designs) before fieldwork.
If we already work with AECOM / Turner & Townsend / Jacobs / RPS Group / CCI System, how do you fit in?
We complement those relationships. Use us for high-volume triage and shortlisting; bring traditional partners in for deep dives on the finalists or for owner’s-rep scopes.
Why exclude pure platforms in this comparison?
Because the decision you need is service-based: a go/no-go with next steps you can execute. Platforms tend to be data holders; they seldom own the workflow or stand behind the decision.
What security and compliance posture do you operate under?
We’re built as an enterprise-grade service with appropriate controls, and we continually automate internal operations to improve consistency and auditability.
How do you measure success?
Lead indicators: time-to-shortlist, qualified sites per week, and cost per qualified site. Lagging indicators: time-to-LOI and hit rate to NTP.
Do you work outside the U.S.?
Yes—we operate across major asset classes and geographies; digital infrastructure is a core focus alongside industrials and telecom.
What deliverables will the IC see?
A consistent scorecard and map pack per site, a weekly roll-up of pipeline quality, and a short appendix with citations a board can trust.
What’s the minimum engagement?
We typically start with a 10–20 site sprint to prove velocity and accuracy, then scale to 100+.
How does pricing work?
Per-site packets priced to reflect automation leverage; total cost per qualified site is materially lower than traditional models at similar quality.
How quickly can you spin up?
We can begin same-day after a short intake. Our forward-deployed teams work alongside you and deliver value immediately.
The leadership case: future-proof your pipeline
In a rapidly changing CRE landscape—constrained grids, hybrid work, accelerating AI demand—an AI-driven, service-backed approach isn’t just a competitive edge; it’s becoming the new normal. Build’s agentic service model places you ahead of the curve today, so you can lead the market tomorrow.