Data vintage 2026-Q1
12 India cities · Single self-contained file, sovereign data
By Srivantage · Eindhoven, NL · capvanta.ai

"Know before you commit — scored, benchmarked, and board-ready feasibility intelligence for your India GCC or AICC decision."

Self-served
No SaaS login
Sovereign data
Affordable
EU AI Act & DPDPA aligned
Mercer · JLL · NASSCOM benchmarks
PDF · DOCX · PPTX export
▶ Evaluate Capvanta — Try the Platform Free trial · No login required · capvanta.ai/#products
Tool 1 · GCC Formation + AI Readiness
GCC 4.0 DIP
Global Capability Center formation with AI readiness scored from Day 1
Objective
Determine whether a GCC is feasible, which India city wins, what it will cost, and what the 5-year ROI looks like. Scores operational foundations alongside AI readiness as a first-class dimension — board-ready before capital is committed.
Instant · Sovereign · Self-served · Affordable
Tool 2 · AI Competency Centre
AICC DIP
AI-native AI Competency Center — pure AI delivery, no GCC operations baseline
Objective
For organisations building a dedicated AI Competency Centre — no prior GCC assumed. Determines whether you can launch AI-native on Day 1, with AI talent, data maturity, and governance as the primary scoring dimensions.
Instant · Sovereign · Self-served · Affordable
Tool 3 · AI Augmentation
GCC iDIP
Augment your existing traditional GCC into an AI intelligence centre
Objective
For organisations with an existing traditional India GCC. Determine whether it can be augmented into an AI capability centre — which archetype fits, what it costs incrementally, and whether it can skip the back-office foundation phase.
Instant · Sovereign · Self-served · Affordable
Foundation capabilities — present in all three tools
Every Capvanta report includes these sections regardless of which tool you run
📊
Scored Feasibility Report
Weighted dimension scorecard, 0–100 overall score, verdict with hard override logic, board-ready executive summary.
📍
City Intelligence — 12 Hubs
Composite ranking across all 12 India hubs. Domain-fit bonus, GPU tier, attrition credit, state policy momentum, scalability gate.
💰
5-Year ROI Model
Cumulative cost vs value, break-even month, sensitivity analysis. Salary: Mercer TRS 2026. Real estate: JLL Q1 2026.
🤝
SI Partner Fit Matrix
15+ providers scored — Accenture, Infosys, Wipro, ANSR, Capgemini and others — against your headcount, model, and domain profile.
👥
Talent & Attrition Benchmarks
City attrition by role (engineering / ops / AI). Salary benchmarks by band. Tier-1 vs Tier-2 comparison. University pipeline.
🏛
Tax & SEZ Intelligence
Section 10AA benefits, Finance Act 2026, state incentive programmes, GIFT City IFSCA. Incentive savings estimate per city.
⚖️
DPDP & GDPR Compliance
GDPR ↔ DPDPA gap matrix, cross-border transfer obligations, EU AI Act × DPDPA regulatory sync score for EU-HQ profiles.
📋
Board-Ready Output Suite
PDF · DOCX · PPTX · Executive one-pager · Board email. All generated client-side in seconds.
🗂️
Next Steps & Action Register
Post-board-approval action plan with sequenced milestones, owners, and timeline. Board-ready cheat sheet for programme kick-off.
✏️
Edit & Customise Reports
Every section is independently editable in the browser. Rewrite any narrative, adjust any finding, add client context — the report becomes yours before you share it.
🎛️
Sensitivity Analysis — What-If
Adjust attrition rate, salary growth, FX rate, and productivity ramp interactively. Instant recalculation across ROI, break-even, and NPV — no re-run required.
🤖
AI Narrative & Report Ask Buddy
Optional AI enrichment generates bespoke narrative paragraphs for every section. Report Ask Buddy answers questions about your specific report in context. BYOK — use your own Groq, Gemini, Claude, or GPT-4o key.
GCC 4.0 DIP — what's unique
7-dimension GCC scorecard — Strategic fit (20%), Talent (18%), Cost & ROI (15%), AI Readiness (15%), Risk & Governance (13%), Location (11%), Execution (8%). AI Readiness is weighted equal to Cost — not a Year-2 add-on.
GCC AI Architecture blueprint — dedicated vs embedded vs hybrid CoE, AI headcount share, MLOps platform guidance, GCC → AICC evolution path and readiness timeline.
Model fit assessment — Captive / BOT / Managed / JV / Hybrid evaluated against your objective, size, sponsor, and timeline. Structural mismatches flagged before board sign-off.
Scoping & L1/L2 design — function-level workstream decomposition, insource vs outsource analysis, hybrid workforce readiness scoring.
Agentic AI Readiness — city composite of GenAI depth, MLOps maturity, PhD density, and GPU tier. Signals whether the chosen city supports a GCC 4.0 AI workload from Day 1.
GCC 4.0
AI Architecture
Model Fit
L1/L2 Scoping
GPU Scoring
AICC DIP — what's unique
8-dimension AICC scorecard — adds Agentic Readiness (6%) as a dedicated dimension. AI Talent (18%) and AI & Data Readiness (16%) weighted higher. GPU factors into both Agentic and Location dimensions.
Cognitive Readiness Score (0–100) — "can this organisation launch AI-native on Day 1?" Data & MLOps (35%), AI Maturity (25%), Governance (20%), City AI Talent (20%). Hard caps for siloed data and absent governance.
Synthetic Data Assessment — scores whether the AICC can operate if HQ data cannot cross borders. Necessity: Required / Recommended / Optional. Critical for EU-HQ profiles under GDPR Art. 49.
AICC team architecture — AI Director hiring guidance, MLOps platform selection, hiring wave sequencing, use-case backlog framework. Greenfield AICC playbook.
AI-weighted city ranking — GenAI skill density, GPU infra, and policy momentum reweighted for pure AICC mandates. Bengaluru and Hyderabad consistently lead.
Cognitive Readiness
Agentic Score
Synthetic Data
GPU × 2 Dims
AICC Architecture
GCC iDIP — what's unique
4 AICC archetypes — ⚙ Efficiency Engine, 🚀 Product Powerhouse, 🧠 Cognitive Core (Corporate Brain), 🧲 Talent Magnet. Each reweights dimensions and generates archetype-specific city advice, team design, and ROI model.
Cognitive Readiness Score — "can this GCC skip the back-office phase?" Five labels: AI-Native Ready → Not Ready. Scores the existing GCC as launchpad, not a greenfield assumption.
GCC Leverage Analysis — quantifies existing GCC value: shared entity saves 30–35% capex vs greenfield, talent pipeline, domain knowledge, governance already in place.
Augmentation ROI model — incremental capex on existing base, shared services discount, side-by-side GCC + AICC financials. Break-even typically faster than greenfield AICC.
Dual-track city recommendation — GCC operations city may differ from optimal AICC hub. Both scored independently; split vs co-location decision surfaced with cost implications.
Augmentation Gantt & failure modes — phased roadmap: Foundation → Architecture → Scale → Optimise, with board gates and hiring triggers. Failure-mode scenario analysis: the top 5 reasons AICC augmentations fail, scored against your profile.
4 Archetypes
Cognitive Readiness
GCC Leverage
Augmentation ROI
Dual-Track Cities
Synthetic Data
12
India Cities Scored
6 Tier-1 hubs + 6 Tier-2 emerging markets across North, South, East and West India.
0
Cloud Dependencies
Single self-contained file. Sovereign data — nothing leaves your browser. No login, no upload, no subscription.
5
Report Formats
PDF · DOCX · PPTX · Executive one-pager · Board email — generated client-side in seconds.
2026‑Q1
Data Vintage
Mercer TRS, JLL Q1 2026, NASSCOM 2026, RBI Apr 2026. Built-in staleness alert after 120 days.
City coverage
Bengaluru ★ Hyderabad ★ Mumbai ★ Pune Chennai Delhi NCR Ahmedabad Kochi Coimbatore Jaipur Indore Chandigarh
★ GPU-Ready (hyperscaler + co-lo)
■ GPU Available (cloud AZ present)
Time-To-Market Intelligence
Three dimensions that make
your reports board-ready
GPU & Compute Infrastructure
Feasibility is no longer just about people. Every city rated None → GPU-Ready. Scored into Agentic Readiness (15%) and Location (20%) dimensions. For AICC, GPU factors into two separate dimensions — higher effective weight than GCC.
EU AI Act × DPDPA Regulatory Sync
EU-HQ profiles receive a tension score where EU AI Act 2026 enforcement conflicts with India DPDPA 2023 consent obligations for AI training data. Dual-framework action plan across all three tools.
Synthetic Data Assessment
"Can the GCC or AICC operate if HQ data cannot cross borders?" Necessity (Required / Recommended / Optional) and feasibility scored against current data architecture. Critical for EU-HQ under GDPR Art. 49.