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AI can help with specific last-mile decisions—such as forecasting demand, planning routes, tracking shipments and choosing among delivery providers—but available evidence does not show that it has universally transformed delivery for Indian direct-to-consumer (D2C) startups or quantify a typical cost saving. For a D2C operator, its value depends on whether these tools improve decisions across the brand’s actual service areas, shipment mix and delivery partners.
How is AI used in last-mile delivery in India?
Last-mile delivery is the leg that moves an order from a local delivery facility or hub to the customer. AI and related logistics software can support several distinct tasks along that leg. The capability is not the same as a proven result: the evidence below describes systems and deployments, not independently measured gains for Indian D2C startups.
- Demand forecasting: Estimate where and when delivery capacity may be needed, helping logistics teams plan resources.
- Route planning: Optimize delivery sequences as route conditions and available capacity change.
- Shipment visibility: Provide tracking and delivery-status information, sometimes alongside digital proof of delivery.
- Provider allocation: Evaluate available delivery supply and select a provider against criteria such as cost, time and reliability.
These functions may be part of a larger transportation-management or delivery platform; calling a system AI-enabled does not, by itself, establish how much it improves performance.
Can one integration connect a D2C brand to multiple delivery companies?
ONDC describes its Open Delivery Protocol as a single integration through which sellers, brands, marketplaces and platforms can access and manage multiple last-mile providers. ONDC says its dynamic routing evaluates available supply and selects a provider across cost, time and reliability. It lists Prorouting, Ola, Uber, Shiprocket, Loadshare, Airxy, Bounce and Delhivery as live network participants.
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ONDC’s current page, accessed in 2026, reports 70+ live logistics service providers and coverage in 150+ cities, as well as 45+ small fleet operators, 50K+ merchants and 50+ brands. These are ONDC’s own reported figures, not independently audited counts. Network participation does not establish that each provider serves every pin code, or that a brand will receive a lower price or better delivery performance. Verify availability and fit for the specific locations and shipment types you serve.
For an operator, the potential benefit is less need to build and maintain separate connections to every participating provider, plus a way to choose among providers available through the network. The practical value still depends on integration work, coverage and the quality of service options in the brand’s operating areas.
What has India Post digitized?
In a Ministry of Communications release dated July 30, 2025, India Post described upgrades to shipment tracking, electronic proof of delivery, OTP authentication, digital payments and open API integration. The department also said it had launched 344 centralized delivery centres in Phase 1. Sunday, holiday, morning and evening delivery options were described as planned capabilities for those centres, not as confirmed availability at every location.
The same release said more than 86,000 post offices were using the new application at the time. It set a target to migrate approximately 165,000 post offices by August 4, 2025; that dated target should not be read as confirmation that migration was completed. The release also described a data analytics team working with IT 2.0 to support route optimization, smart sorting and demand forecasting. These are program descriptions from the department, not independent measurements of delivery outcomes.
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What does a real AI-enabled logistics deployment show?
Delhivery’s FY2024–25 annual report describes Project Disha, a meal-distribution operation for The Akshaya Patra Foundation. Delhivery says its AI-powered TransportOne transportation-management system was deployed across all 78 Akshaya Patra kitchens, enabling live driver tracking and real-time route optimisation across 1,440 daily routes.
This is a company-reported example of logistics software operating at substantial scale, but it concerns school-meal distribution rather than a D2C startup. It does not establish what a small brand would achieve, and the report’s extracted annual-savings figure is not reliable enough to quote. Separately, Delhivery reported a footprint of 4,494 last-mile delivery centres, including partner centres, as of March 31, 2025. That footprint figure describes the company’s network, not a performance result or a guarantee of service in a particular pin code.
Can AI reduce delivery costs for a D2C startup?
The available evidence does not establish a typical AI-driven cost reduction for Indian D2C last-mile delivery. ONDC describes provider selection across cost, time and reliability, while the Delhivery example reports capabilities in a different kind of operation; neither supplies an independent, startup-specific comparison showing savings against a baseline.
A brand assessing a cost claim should ask what was compared, over what period and geography, and whether the calculation includes delivery failures, customer contact, returns, COD handling and integration costs. A lower quoted charge per shipment is not necessarily a lower total delivery cost if service quality or reattempts differ.
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How should a D2C brand compare logistics options?
The following is a practical comparison framework, not an official ranking or standard. Test options against the brand’s own orders and service requirements rather than relying on a general claim about AI or network size.
- Serviceability: Check pin-code coverage, including the specific remote or rural areas where customers order.
- Total cost: Compare charges for the brand’s shipment profiles and service levels, and account for failed deliveries, reattempts, returns and COD reconciliation where relevant.
- Delivery performance: Evaluate delivery time and reliability for the locations and periods that matter to the business.
- Exception handling: Check how providers handle failed delivery attempts, customer contact and proof of delivery.
- Visibility and integration: Assess tracking detail, data access and the work required to connect delivery updates to the order system.
- Payments: Confirm how COD collections, settlements and reconciliation are handled.
- Flexibility: Establish how easily the brand can add, change or remove providers if coverage, cost or service changes.
India Post’s 2025 release describes tracking, proof of delivery, OTP, APIs and COD-related integrations; ONDC describes dynamic provider selection using cost, time and reliability. The remaining checks above are practical operator considerations, not claims that either source prescribes a particular procurement method.
What the evidence does—and does not—establish
Official descriptions document concrete logistics capabilities, and Delhivery’s annual report provides a provider-reported deployment example. They do not establish an independent statistic for AI adoption or measured AI impact among Indian D2C last-mile operators. In particular, they do not show how much AI changes delivery costs, speed, failed-delivery rates or returns for that group.
The Ministry’s July 30, 2025 statements about India Post are government descriptions of a program. The minister said the enhancements must enable India Post to offer “seamless, end-to-end logistics services comparable to those of leading market players”; that is an aim, not proof that the target has been met. ONDC’s network figures and Delhivery’s case are likewise attributable to those organizations, rather than independent evaluations.
ONDC lists Shiprocket and Delhivery among its live logistics participants, and Delhivery describes its TransportOne platform in its annual report. These are informational examples, not endorsements; a brand should verify current availability and suitability directly.
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