Overview

Freight Tiger, a leading logistics technology platform connecting shippers and transporters across India, set out to operationalize GenAI across its business—powering predictive ETAs, intelligent copilots, and automated document processing.

Like many fast-growing enterprises, Freight Tiger quickly discovered that GenAI is easy to prototype, but exceptionally hard to scale without a unified, governed data foundation. Fragmented data, rising infrastructure costs, and governance gaps turned innovation into friction.

Koantek partnered with Freight Tiger to reset the foundation, modernizing the data platform, restoring trust in data, and unlocking GenAI at enterprise scale.

Business Impact at a Glance‍

1. Sustainable Economics at Scale:
30–50% reduction in TCO, 30–40% faster processing, and 100% increase in reporting capacity
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2.Single Source of Truth:

‍Unified, governed data foundation that restored organizational trust and enabled confident, data-driven decisions
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3. GenAI Innovation Unlocked:
Three production-grade AI/ML capabilities deployed—automated document processing, predictive ETAs, and natural-language insights‍

4. Speed Without Disruption:
Two platform migrations completed in under 90 days with zero downtime—3× faster than industry benchmarks

Challenges Faced by the Customer

GenAI Blocked by Legacy Foundations

Freight Tiger faced systemic challenges common to high-growth enterprises:
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Fragmented Data Landscape

• Data spread across teams, tools, and cloud environments
• Redundant pipelines and inconsistent definitions
• No trusted source of truth for business-critical metrics
• Analytics and operations teams working from conflicting data

GenAI Scaling Barriers

• POC paralysis: pilots unable to move into production
• Model trust issues: fragmented data degrading accuracy
• Cost explosion: infrastructure spend rising faster than value
• Governance gaps: compliance and risk constraints blocking scale

How Koantek Responded

Koantek led a strategic modernization initiative, not a lift-and-shift migration—anchored in business value, disciplined prioritization, and long-term scalability.

Strategic Foundation

Before migrating a single workload, Koantek partnered with Freight Tiger to:

• Identify high-value GenAI and analytics use cases
• Map data domains and dependencies
• Decide what to migrate, modernize, or retire
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  The result: a deliberate reset of the data foundation aligned to business outcomes.

Phase 1: Design

• End-to-end architecture and workload assessment
• X2D-based modernization roadmap

Phase 2: Migration & Execution

• Automated SQL transpilation
• Optimized pipeline reconstruction
• Parallel validation to ensure data integrity

Phase 3: Stabilization & Governanace

• Performance tuning for cost and speed
• Centralized governance via Unity Catalog
• Enablement and knowledge transfer for internal teams

Koantek executed two complex migrations from Snowflake to Databricks, followed by Databricks on Azure to Databricks on AWS with zero downtime throughout. Advanced accelerators including X2D, Lakebridge, Delta Lake, and Unity Catalog compressed timelines and minimized risk.

Results

Time to Value

• Full transformation from assessment to production in under 90 days
• 3× faster than the typical 6–9 month migration cycle
• Zero downtime across sequential platform transitions

Financial & Performance Gains

• 30–50% reduction in total cost of ownership
• 30–40% faster data processing
• 100% increase in reporting capacity

Strategic Enablement

• Enterprise-ready GenAI foundation
• Restored trust in data accuracy and consistency
• Platform built for rapid, repeatable innovation

What's Next: GenAI in Production

With a modern data foundation in place, Freight Tiger rapidly deployed three high-impact GenAI and ML capabilities:

1. Automated Document Classification & Extraction
2. Streamlined logistics paperwork with higher accuracy and minimal manual intervention, significantly reducing operational friction.
3. Predictive ETA Models
4. Advanced forecasting using historical data, real-time traffic, weather signals, and vehicle telemetry to improve customer experience and operational planning.
5. Natural-Language Insights Interface
6. Plain-English data querying that democratized access to insights and accelerated decision-making across the organization.

Testimonial

“Koantek demonstrated a strong ability to navigate the complexity of our data ecosystem from day one. Their work went far beyond migration — encompassing architectural rationalization, governance alignment, and performance optimization that fundamentally strengthened our data foundation. What stood out was their consultative rigor. The team asked the right architectural questions, identified gaps early, and proactively surfaced risks before they became blockers. Their guidance on clustering strategies, partitioning design, and Unity Catalog integration ensured every decision was deliberate and future-ready. They also helped us build data readiness for GenAI — ensuring our datasets are structured, governed, and positioned to support advanced analytics and AI initiatives. The team's ownership, transparency, and collaborative working style instilled confidence throughout every complex transition. We strongly recommend Koantek to any organization looking to modernize their data platform and build a solid foundation for AI-driven outcomes."

-Ritesh Anand, Sr. Engineering Manager - Data
Frieght Tiger