ATRC REMOTE SUPPORT

AI Data Center
Full Lifecycle Services.

Pre-Feasibility → Feasibility → CBA → Design → Build → Support → Training → Software
Rented Racks · In-House Build · New Location — Across 7+ Global Regions

From Pakistan to the UK, Australia, Africa, and Qatar — we deliver the complete lifecycle: feasibility studies, cost-benefit analysis, architectural design, hardware implementation, managed support, training, and custom software development for any AI model or application.

Remote Support LLC · Khawar Nehal, Founder & CTO Full Lifecycle Brochure · Version 4.0 · 2026
7+ Regions · 3 Deployment Models · 9 Service Lines
Service Lifecycle

The Complete 9-Stage Lifecycle

Every AI data center engagement follows a structured lifecycle. We can deliver any stage independently or as a full turnkey program.

1Pre-FeasibilityOpportunity & risk scan
2Feasibility StudyTechnical & economic viability
3Cost-Benefit AnalysisTCO, ROI, NPV, IRR
4Design & ArchitectureHLD, LLD, engineering
5ImplementationProcure, build, integrate
6Support & Operations24/7 SLA-backed
7TrainingAdmin & end-user
8Software DevCustom apps & integrations
9OptimisationContinuous improvement

Engagement Flexibility

Engage us for a single stage (e.g., feasibility study only), a phase (design + implementation), or a full turnkey program. Every stage has defined deliverables, acceptance gates, and pricing.

Stage 1 & 2

Pre-Feasibility & Feasibility Studies

STAGE 1

Pre-Feasibility Study

A rapid, low-cost assessment to determine whether an AI data center investment is worth pursuing further.

  • Opportunity scan: Business drivers, AI use cases, and demand assessment
  • Site shortlisting: Regional options (rented/in-house/new) with high-level power, cooling, and connectivity checks
  • Regulatory screening: Data sovereignty, export controls, and local compliance
  • Budget envelope: Order-of-magnitude CAPEX and OPEX estimates (±30–50%)
  • Risk register: Top 10 risks with probability/impact/mitigation
  • Go/No-Go recommendation with a decision framework
Deliverable: Pre-Feasibility Report (20–30 pages) · Duration: 2–4 weeks · Example: A Qatari conglomerate screened 3 regions and eliminated 2 due to grid constraints, saving $80K in wasted design fees.
Target customers: Boards, CFOs, and strategy teams deciding whether to invest.
STAGE 2

Feasibility Study

A detailed technical and economic viability assessment before committing to design and procurement.

  • Technical feasibility: Power availability, cooling capacity, floor loading, network latency, and GPU supply chain
  • Site readiness survey: Rack space, kW power, cooling headroom, and physical security
  • AI workload assessment: Model sizes, concurrency, context windows, and storage requirements
  • Regulatory & legal review: Data residency, PDPA/CLOUD Act/GDPR, and export compliance
  • Vendor & supply chain assessment: GPU lead times, regional distributors, and refurbished options
  • Implementation roadmap: 16–32 week phased plan with critical path
  • Class estimate CAPEX/OPEX (±15–20% accuracy)
Deliverable: Feasibility Study Report (60–90 pages) + Financial Model · Duration: 4–8 weeks · Example: A UK fintech's feasibility study revealed London grid delays would push go-live by 14 months; we pivoted to Manchester and saved 10 months.
Target customers: CTOs, infrastructure heads, and project sponsors preparing a business case.
Stage 3

Cost-Benefit Analysis (CBA)

STAGE 3

Cost-Benefit Analysis & Financial Modelling

A rigorous, investor-grade financial model to justify the investment and compare deployment options.

  • Total Cost of Ownership (TCO): 5-year and 10-year CAPEX + OPEX across all scenarios
  • CAPEX breakdown: Hardware BOM, facility build, integration labor, taxes/duties, contingency
  • OPEX breakdown: Colocation, power, cooling, support, warranty, staffing, storage expansion
  • ROI / NPV / IRR / Payback Period under base, optimistic, and pessimistic cases
  • Scenario comparison: Rented vs. in-house vs. new location; region vs. region
  • Currency & sensitivity analysis: USD/PKR/MYR/GBP/AUD exposure and inflation
  • Benefit quantification: Productivity gains, risk reduction, compliance value, and revenue enablement
  • Financing options: CAPEX vs. OPEX models, lease vs. buy, and tax incentives (MDEC, UK super-deduction, etc.)
Deliverable: Excel Financial Model + CBA Report · Duration: 3–6 weeks · Example: For a South African bank, our CBA showed a 22% 5-year TCO advantage for rented racks in Johannesburg vs. an in-house Cape Town build — NPV positive in Year 3.
Target customers: CFOs, investment committees, and boards requiring a defensible business case.

Sample CBA Output (Illustrative)

Metric Rented Racks In-House Build New Location
5-Year TCO$4.1M–$4.8M$4.3M–$4.9M$4.5M–$5.2M
Deployment Timeline16–20 weeks24–32 weeks30–40 weeks
Payback Period2.8 years3.5 years3.9 years
NPV (8% discount)$1.2M$0.9M$0.7M
IRR28%21%18%

Figures are illustrative and vary by region, scale, and model mix. Full CBA delivered per engagement.

Stage 4

Design & Architecture

STAGE 4

High-Level Design (HLD) & Low-Level Design (LLD)

Complete engineering documentation for your AI data center — from cluster topology to cable schedules.

  • Distributed 5-cluster architecture: API/Orchestration, Vector DB, LLM Inference, ETL, Batch Multimedia
  • Network design: 100GbE spine-leaf fabric, zero-trust segmentation, air-gap boundaries
  • Memory & storage hierarchy: HBM3e sizing, DDR5 allocation, NVMe hot tier, HDD cold tier
  • Power & cooling engineering: kW/rack calculations, liquid vs. air cooling, UPS/generator sizing
  • Security architecture: RBAC matrix, audit logging, offline update protocol
  • Data sovereignty map: Where data lives, flows, and is backed up
  • LLD deliverables: BOM with unit rates, rack layouts, IP schema, cable schedules, commissioning plan
Deliverable: HLD + LLD packages (editable formats) · Duration: 4–8 weeks · Example: Our HLD for a Kenyan fintech specified 8-GPU H200 nodes with direct-to-chip cooling, avoiding a $200K overspend on unnecessary redundancy.
Target customers: Infrastructure architects, construction partners, and procurement teams.
Stage 5

Implementation & Deployment

STAGE 5

Procurement, Build & Integration

End-to-end delivery: hardware sourcing, installation, commissioning, and live integration.

  • Hardware procurement: GPU servers, CPU nodes, storage, networking, and software licenses
  • Supply chain management: Import handling, customs clearance, SBOM verification, and country-of-origin documentation
  • Facility preparation: Racking, power distribution, cooling commissioning, and physical security
  • Cluster deployment: All 5 clusters installed, configured, and tested
  • MCP connector development: Read-only integrations to 10 enterprise systems
  • Data ingestion: ETL pipelines, embedding generation, and vector DB population
  • Acceptance testing: Air-gap validation, 50-concurrent-session latency, citation accuracy, RBAC, backup/restore
  • Go-live & handover: SLA baseline measurement and formal transition to operations
Deliverable: Commissioned system + Acceptance Test Report + Go-Live Certificate · Duration: 12–16 weeks (post-design) · Example: A Malaysian logistics firm went from contract to production in 18 weeks, integrating 10 legacy systems with zero data loss.
Target customers: Organizations wanting a single accountable partner for the entire build.
Stage 6

Support & Managed Operations

STAGE 6

SLA-Backed Support & 24/7 Operations

Keep your AI platform running at peak performance with proactive monitoring and rapid incident response.

  • 8x5 business-hour support (baseline): Remote monitoring, patch management, and quarterly SLA reports
  • 24x7 severity-based escalation (optional): Critical incident response with 4-hour SLA
  • Hypercare (Weeks 17–20): Enhanced monitoring and weekly status reviews post-go-live
  • Offline patch & model updates: Quarterly or as-needed delivery via secure transfer station
  • Backup & disaster recovery: Scheduled drills, restore testing, and immutable backups
  • Capacity planning: Storage expansion, GPU scaling, and performance tuning
  • 99.9% uptime SLA: Proportional service credits applied automatically
Deliverable: Monthly/quarterly SLA reports + 12-month warranty · Example: A Qatari enterprise maintained 99.95% uptime over 12 months with our proactive monitoring and hypercare.
Target customers: Organizations without in-house AI ops teams, or those seeking SLA-backed peace of mind.
Stage 7

Training & Knowledge Transfer

STAGE 7

Admin & End-User Enablement

Build internal competency so your team can operate, maintain, and extend the platform independently.

  • Train-the-trainer: 3–5 administrators, 2–3 days on-site
  • Operator onboarding: 1–2 days for end-users (50 authorized users)
  • Curriculum: System architecture, daily operations, incident escalation, offline update protocol, backup/restore, RBAC administration
  • User curriculum: Basic usage, prompt engineering, understanding citations and uncertainty notices
  • Documentation package: Architecture diagrams, operations manual, troubleshooting guide, user guide, offline update protocol manual
  • Recorded sessions: Walkthroughs of critical procedures for future reference
Deliverable: Training Completion Certificate + Documentation Package + Recorded Sessions ·