What does Cobbled Climbs do

Cobbled Climbs is a Mumbai-based premium cycling retailer and India's exclusive distribution partner for Rapha, MAAP, and Pas Normal Studios. The catalogue covers 10,000+ products across 250+ brands, ranging from race-grade apparel to components and accessories.

What problem did Calibrate solve for Cobbled Climbs

Content production was the bottleneck. With 10,000+ products and 250+ brands across multiple categories, the manual workflow could not keep up with launches, seasonal collections, and brand-specific content needs. Cobbled Climbs needed a system that could generate consistent, on-brand content at the rate the catalogue moved.

CC-360 (also called CC Content OS) is a custom Next.js content automation dashboard built for Cobbled Climbs. It connects to the Shopify catalogue, ingests product data, and uses Claude Code as the orchestration layer to generate carousels, product descriptions, blog content, and social posts, all in Cobbled Climbs brand voice.

What tools and technologies did Calibrate use

The stack is Next.js for the dashboard, Shopify for product data, Claude Code as the AI orchestration layer, and the Strava API for community and ride content. Metricool handles social distribution. The architecture is designed so additional content surfaces such as email and paid ads can be added without rebuilding the foundation.

Why is Calibrate showing its own founder's business as a case study

Because that is where the system was first proved. CC-360 was built for Cobbled Climbs by Prashant Kochhar, who is also Calibrate's founder. The system worked, scaled, and became the seed concept for Thea AI, a separate SaaS platform Calibrate is now developing. Using a real proving-ground project is more transparent than commissioning a fictional or anonymous example.

Can Calibrate build a similar system for my business

Yes, with caveats. Custom content engines like CC-360 work best for businesses with structured product or content data and a clear brand voice. The build timeline is typically 8 to 16 weeks depending on integration complexity. The fastest way to scope is the audit request form on the contact page.

Case Study

Cobbled Climbs

India's exclusive partner for Rapha, MAAP, and Pas Normal Studios — a Mumbai-based premium cycling specialist with 250+ brands with over 5,000 sku's. The brief: become the brand AI search recommends, in a category dominated by Decathlon, Trek, and budget marketplaces.

Year:

2025

Industry:

Retail & E-commerce

Engagement:

90-day visibility program

Live website:

https://cobbledclimbs.com

The Problem

AI search broke the premium cycling funnel. ChatGPT, Perplexity, and Google AI weren't recommending Cobbled Climbs — they defaulted to Decathlon and Trek for queries Cobbled Climbs should have owned.

Cobbled Climbs has authentic premium positioning — exclusive Rapha, MAAP, and PNS partnerships, 250+ brand catalog, deep category authority. None of that was reaching AI search engines. The brand was invisible in the queries that decide where buyers go. Three structural problems: - No entity recognition: AI engines didn't connect 'Cobbled Climbs' to 'premium cycling in India.' - Schema gaps: Product, brand, and review markup was thin or missing. - Zero share-of-voice signal: No category-defining content outside the brand's own domain meant no citation authority.

AI visibility uplift (90 days)

+42%

AI visibility uplift (90 days)

+42%

AI visibility uplift (90 days)

+42%

Brand mentions (90 days)

175K+

Brand mentions (90 days)

175K+

Brand mentions (90 days)

175K+

Avg position, cycling stores India

Solution

We applied Citation Architecture™ — Calibrate's framework for engineering brand citation across AI engines. Schema, entity work, share-of-voice content, and category authority built into the brand's foundation, not bolted on.

Over 90 days we ran four parallel workstreams: - Entity work: connected 'Cobbled Climbs' to 'premium cycling India' across schema, content, and structured data — so AI engines could resolve the brand to its category. - Citation-first content: built 53 topic clusters around real buyer queries (the actual prompts buyers type into ChatGPT and Perplexity). - Share-of-voice authority: secured brand mentions across the third-party properties AI engines crawl for context. - Real-time tracking: monitored 30+ buyer queries across 6 AI engines daily via Searchable, iterating based on what moved. Compound effect: AI engines stopped defaulting to mass-market brands and started recommending Cobbled Climbs as the premium answer.

Testimonial

We built Citation Architecture™ on Cobbled Climbs first — our own e-commerce brand. No client budget, no agency excuses. These are the real numbers that gave us the right to charge anyone else for this work.