Per discipline, per bid
One engineer manually cross-references a single discipline against the spec. Electrical alone can swallow a full day.
Conformance review · Data center design
Every spec, checked.
Every gap, caught.
ADDCR reads a data center owner's design spec, reads the bidder's engineering drawings, and reviews one against the other — flagging every missed requirement and confirming everything that's satisfied. What takes an engineer 12 hours per discipline, ADDCR does in minutes.
- Drawing × spec cross-referencing
- Discipline-by-discipline coverage
- Auditable, citable findings
12h → min
Per-discipline review time, collapsed
100%
Of spec line-items checked, every time
6+
Engineering disciplines reviewed in parallel
0missed
Requirements lost to reviewer fatigue
01 — The bottleneck
A single proposal can take days to read.
When a hyperscaler issues a data center design spec, every bidder submits engineering drawings meant to satisfy it. Someone has to confirm they actually do — line by line, discipline by discipline.
Multiplied by every bidder
Each proposal repeats the same exhaustive read. Reviewer time scales linearly with the size of the field.
And humans get tired
Buried clauses get skimmed. A missed requirement late in review is a costly change order — or a failed build — later.
02 — How it works
Spec in, drawings in, conformance out.
-
01
Ingest the spec & the set
Upload the owner's design specification and the bidder's drawing package. ADDCR parses both into structured, addressable requirements and details.
spec.pdf · drawings.dwg/pdf → parsed -
02
Cross-reference each discipline
For every requirement, ADDCR locates the corresponding evidence in the drawings and decides: satisfied, missing, or needs review — with a citation back to the source.
requirement ⇄ drawing evidence -
03
Return an auditable report
You get a conformance report: green ticks for what's met, flags for what's missed, each linked to spec clause and drawing location so your engineers verify in minutes, not days.
report.json · findings + citations
03 — Coverage
Every discipline, reviewed in parallel.
Each discipline that used to be a separate engineer-day is reviewed simultaneously.
Electrical
Redundancy, UPS & generator sizing, coordination, grounding, arc-flash.
Mechanical & Cooling
CRAC/CRAH capacity, redundancy, airflow containment, chilled water.
Structural
Floor loading, seismic, raised-floor & equipment support criteria.
Fire & Life Safety
Detection, suppression, egress, compartmentation per code.
Power Distribution
PDU/RPP layout, busway, capacity headroom, metering.
Telecom & Pathways
Cable routing, tray fill, separation, MMR/MDA provisioning.
04 — The output
A report your engineers can trust and act on.
Electrical 18/19
Mechanical 22/24
Structural 11/11
Fire & Life Safety 14/17
Power Dist. 9/9
Telecom 7/7
SATISFIEDM-2.03
CRAH units provide N+1 redundancy at design day load.
Spec §4.2.1 · Drawing M-201, schedule note 3 · 6×(N=5)+1 confirmed
MISSINGFLS-3.10
Pre-action sprinkler interlock with VESDA detection not shown.
Spec §7.4 requires double-interlock · No corresponding detail located in fire set
REVIEWM-2.14
Chilled water ΔT stated as 10°F; spec targets 12°F.
Spec §4.3.2 · Drawing M-410 note 1 · Confirm impact on pump & pipe sizing
Every finding cites the spec clause and the drawing location — so review becomes verification.
05 — Data residency
Your drawings never leave your servers.
Specs and engineering drawings are some of the most sensitive IP a firm holds. ADDCR is built to run inside your own environment — your data stays on your infrastructure, under your control, the whole way through review.
- Complete data residency. Deploy ADDCR in your VPC or on-prem. Documents are processed where they live and never transit our servers.
- Your IP stays yours. No training on your data, no retention beyond the review, no third-party sharing — ever.
- You hold the keys. Run against your own model endpoints and storage, with full audit logs of every access.
06 — Who we are
Operators and platform engineers, paired.
Hyperscale operations × large-scale data & AI systems — the two halves of the AI infrastructure problem.
Co-founder · Operations
Hussain Sharif
6+ years designing, deploying, and operating hyperscale data center infrastructure at Microsoft. Brings direct line-of-sight to the operational realities of liquid-cooled AI facilities.
- Data center construction & deployment
- Cooling & power infrastructure coordination
- Hyperscale operational processes
- Facility reliability & capacity planning
- AI infrastructure deployment requirements
- Cross-functional infrastructure operations
Co-founder · Platform
Saif Mahamood
8+ years building large-scale data platforms and distributed systems that turn massive, messy data into reliable, structured signal. Designed and operated mission-critical, high-throughput data and AI infrastructure — the backbone of automated analysis at scale.
- Large-scale data processing pipelines
- Document & telemetry data extraction at scale
- AI / ML data infrastructure & pipelines
- Distributed systems reliability & correctness
- Cloud-native infrastructure & observability
Get started
Bring conformance review down to minutes.
We're onboarding a small group of data center engineering & design teams. Tell us about your spec workflow and we'll set up a review on your own documents.
No spam. We'll only reach out about an ADDCR pilot.