Locus.sh (MARA Labs) Pitch Deck (2015): 11-Slide Seed Deck

See all 11 slides of the Locus.sh pitch deck — a 2015 Seed deck — with a slide-by-slide teardown of what the deck does well and where it falls short.

The Locus.sh (MARA Labs) seed deck is a concise 11-slide presentation from April 2015 that positions the company as a 'Platform as a Service for Logistics Fulfillment.' The narrative leans heavily on the founders' engineering pedigree at Amazon and their ability to solve the 'inelegant' manual intervention required in modern delivery operations. Rather than relying on theoretical B2B traction, the deck uses a consumer-facing app, RideSafe, to demonstrate the efficacy of their proprietary Route Deviation Detection (R2D2) engine. While the deck lacks a formal 'Ask' slide or detailed financial p…

Key takeaways

Introduction and Title Slide

The deck opens on Slide 1 with the original company name, MARA Labs , and a playful recursive acronym: "MARA Ain’t a Routing Algorithm." The subtitle immediately defines the category: "Platform as a Service for Logistics Fulfillment." Dated April 2015 and attributed to Nishith Rastogi, the slide establishes a professional, tech-forward tone with a simple heart-shaped location pin logo.

The Team (Slide 2)

Slide 2 focuses on the founders, Nishith Rastogi (CEO) and Geet Garg (CTO) . The primary value proposition here is their shared history at Amazon. The slide explicitly states they worked together for two years as engineers, building "scalable, externalized, public APIs for Amazon." Their academic credentials from BITS-Pilani and IIT KGP, combined with specific experience in Fraud, ML, and AWS, signal to investors that this is a high-pedigree engineering team capable of handling complex backend infrastructure.

The Problem and Market Pain (Slide 3)

Slide 3 identifies an "Expensive pain point in a Massive Market." It highlights the growing need for better tools in dispatch, resource assignment, and route optimization. The slide calls out that existing solutions are "inelegant & un-optimized," requiring massive manual intervention. A key data point is cited at the bottom: "A staggering 75% of e-commerce customers feel the need for better tracking," providing a clear link between operational inefficiency and poor customer experience.

The Solution (Slide 4)

Slide 4 presents the solution as a "Tool for Automated dispatch, tracking & route optimization." It makes three bold claims: eliminating 90% of human intervention , a 75% reduction in effort when scaling to new cities, and providing live minute-by-minute ETA updates. This slide transitions the deck from identifying a problem to offering a specific, quantifiable efficiency gain.

The Value Proposition (Slide 5)

Slide 5 addresses the "Build vs. Buy" dilemma. Titled "You can’t build this in-house while making financial sense," it argues that MARA Labs absorbs the R&D costs to create high-end algorithms. By offering this as a service with "clean APIs," they allow customers to integrate the solution into their existing stacks without the operational overhead of maintaining a proprietary routing engine.

Use Cases (Slide 6)

Slide 6 uses a hexagonal graphic to illustrate diverse applications for the technology. These include:

Dispatch Assignment: Making station managers obsolete for on-demand delivery. · Tracking of Goods: Using a proprietary route deviation engine. · Schools: Providing live updates and ETAs for school buses to parents. · Food-Tech: Ensuring faster turnaround times for fresh delivery. · Laundry Pick Up: Precise ETAs accounting for live traffic. · E-Commerce: Route optimization for lower costs.

Market Size (Slide 7)

Slide 7 provides "Market Size Indicators." It values the logistics fulfillment industry at $231 billion . It breaks this down geographically, noting a $1.5 billion investment in the US 'Uber for X' economy in 2014 and $400 million invested in Indian food/grocery startups in Q1 2015. It also estimates that just four Indian companies (HealthKart, FabFurnish, YepMe, and Lenskart) account for 10 million deliveries a year, illustrating the sheer volume of transactions available for an API-based service.

Business and Revenue Models (Slides 8-9)

Slide 8 defines the operational flow: Input (locations, times, available drivers) leads to Benefits (optimum routes, task pushing to phones, and live reporting). Slide 9 gets specific about the Revenue Model . The B2B product is branded as "Locus." It uses a subscription model where each API call is charged at a "few (single digit) cents." To reduce friction, the company provides all dashboards and SDKs for free, focusing monetization entirely on the core algorithmic usage.

Proof of Concept: RideSafe (Slides 10-11)

Slide 10 introduces RideSafe , a B2C app built on their B2B APIs to demonstrate the "Realtime Route Deviation Detection (R2D2)" engine. The metrics are impressive for a four-week pilot: 12,000+ KM of usage data and 2,000 users. The slide claims the app ranked #1 on the Play Store in the transport category on Women's Day with zero marketing spend. Slide 11 supports this with a collage of media coverage from Lifehacker, NDTV, and City Express, proving that their core technology has public validation and real-world utility.

What Locus.sh Does Well

The deck excels at establishing Founder-Market Fit . By highlighting their Amazon engineering backgrounds specifically in ML and AWS, the founders position themselves as the exact right people to build a scalable logistics API. The use of a B2C app (RideSafe) as a "reference implementation" is a brilliant way to prove that the technology works in the real world before a single B2B contract is signed. It provides tangible data (220,000 location points) that would otherwise be theoretical in a seed-stage deck.

What is Missing from the Deck

The most notable omission is a specific "Ask" slide . The deck explains what they are building and how they will charge for it, but it does not state how much capital they are seeking or how they intend to deploy those funds. Additionally, there is no competitive landscape slide. While they mention that existing solutions are "inelegant," they do not name specific competitors or explain their technical moat beyond "high-end algorithms." Finally, there are no financial projections or a roadmap showing how they plan to move from a consumer safety app to enterprise logistics contracts.

Founder Takeaways

Founders should emulate the quantified value proposition found on Slide 4. Instead of saying the tool is "fast," Locus claims it "eliminates 90% of human intervention." This gives investors a concrete metric to model. Furthermore, the usage-based revenue model on Slide 9 is explained with extreme clarity—charging per API call while giving away the "wrapper" (SDKs/dashboards) for free is a classic developer-first growth strategy that remains highly effective today. If you are building a B2B infrastructure company, consider building a small B2C "demonstrator" to generate the kind of usage data shown on Slide 10.

Frequently asked questions

What was the original name of Locus.sh?
According to Slide 1, the company was originally named MARA Labs, with the acronym standing for 'MARA Ain’t a Routing Algorithm.' The B2B product itself was branded as 'Locus' (Slide 9).
How does Locus.sh plan to make money?
Slide 9 outlines a B2B Platform as a Service (PaaS) model. They use a subscription model with a card on file, charging a few single-digit cents per API call. Notably, they provide all dashboards, SDKs, and delivery apps for free to lower the barrier to entry.
What is the 'R2D2' engine mentioned in the deck?
As described on Slide 10, R2D2 stands for 'Realtime Route Deviation Detection.' It is their proprietary engine used to alert managers or users when a vehicle veers off its intended path, a feature first validated in their RideSafe consumer app.
What specific metrics did the company share regarding their proof of concept?
Slide 10 notes that their reference app, RideSafe, achieved 12,000+ KM of usage data, 2,000 users, and 220,000+ location points within its first four weeks, ranking #1 on the Play Store in the transport category on Women's Day without marketing spend.
Who are the founders and what is their background?
Slide 2 introduces Nishith Rastogi (CEO) and Geet Garg (CTO). Both are BITS-Pilani or IIT graduates who worked together for two years as engineers at Amazon, specializing in fraud detection, machine learning, and AWS infrastructure.
Cover slide of the Locus.sh (MARA Labs) pitch deck — Seed 2015
Locus.sh (MARA Labs) pitch deck, slide 1 (2015)

Locus.sh (MARA Labs) pitch deck: the facts

Company
Locus.sh (MARA Labs)
Year
2015
Stage
Seed
Slides
11
Sector
Logistics / PaaS
Deck type
Seed Round Pitch Deck
Outcome
Raised Seed Round (Source: External knowledge, not in deck)
Headquarters
India

Locus.sh (MARA Labs) pitch deck PDF

The full Locus.sh (MARA Labs) deck is embedded on this page and can be read slide by slide in the browser — no download or account required. Each slide is covered in the breakdown above.

What the Locus.sh (MARA Labs) pitch deck was used for

This deck is the April 2015 seed-round pitch for MARA Labs’ logistics fulfillment platform "Locus," a PaaS product focused on automated dispatch, tracking, and route optimization for businesses with mobile workforces. At this time the company was transitioning from a consumer safety app toward a B2B logistics engine aimed at e-commerce and "Uber for X" operations. The deck positions Locus as a high‑R&D, algorithms-first platform offered via APIs and subscription pricing, and it was used to raise an undisclosed angel/seed round led by growX Ventures and angels such as Manish Singhal.

Business model: AI-powered logistics management and route optimization platform offered as a platform-as-a-service (PaaS) for dispatch, tracking, and route planning for businesses with mobile workforces.

Round
Seed / angel
Year
2015
Lead investor
growX Ventures
Investors
growX Ventures, Manish Singhal, Bhupen Shah, Amit Ranjan, Sanjay Mehta, Ankit Pruthi
Founded
July 2015
Headquarters
Headquartered in the US with an office in Bangalore, India.
Industry
Logistics technology / dispatch and route-optimization software (SaaS / PaaS).

Raising: Undisclosed seed/angel round closed in July 2015, following use of the April 2015 seed pitch deck.

Total funding: Approximately $76M in total funding across multiple rounds (seed/angel, Series A, pre-Series B, Series B, Series C).

Use of funds as presented: Early sources note the funds were used to build out the logistics management platform Locus, invest in high‑end routing and dispatch algorithms, and expand technology and team capabilities.

What happened after the Locus.sh (MARA Labs) deck

The seed pitch deck supported an undisclosed angel/seed round in 2015; the company subsequently validated its logistics optimization thesis, scaling into a multi-round funded platform with Series A, pre‑Series B, Series B, and Series C financings from prominent venture and strategic investors.

What the Locus.sh (MARA Labs) deck got right

What could have been stronger

How an investor would read this deck

What draws attention

Risks that stand out

Questions this deck invites

What founders can take from the Locus.sh (MARA Labs) deck

Locus.sh (MARA Labs) pitch deck: common questions

What is the purpose of the April 2015 Locus.sh (MARA Labs) pitch deck?

Locus.sh (operated by MARA Labs) used this 11‑slide pitch deck in April 2015 to raise an undisclosed angel/seed round for its logistics fulfillment platform "Locus," a PaaS product that automates dispatch, tracking, and route optimization for mobile workforces.

Who invested in the seed/angel round associated with the Locus.sh pitch deck?

According to coverage of the deck, the angel/seed round was led by Delhi‑based early-stage firm growX Ventures and angel investor Manish Singhal, with participation from Sanjay Mehta, Ankit Pruthi, and Bhupen Shah, among others. VCCircle notes that Locus received seed funding from growX Ventures, Bhupen Shah, Manish Singhal, Amit Ranjan and others in July 2015.

How much money did Locus.sh raise with this seed pitch deck?

The amount raised in the 2015 seed/angel round is undisclosed in the available sources. Later, Locus raised $2.75M in Series A funding in May 2016, $4M in pre‑Series B in June 2018, $22M in Series B in May 2019, and $50M in Series C in June 2021.

What solution does Locus.sh propose in the seed pitch deck?

The deck describes a platform that eliminates up to 90% of human intervention in order dispatch through intelligent algorithms, offers live on-road tracking and minute-by-minute ETA updates, and exposes its functionality via clean APIs on a subscription model where each API call is charged a few cents. It targets e‑commerce, on‑demand delivery, food tech, laundry pickup, and school bus tracking, among other logistics use cases.

What happened after the Locus.sh seed pitch deck—how did the company’s fundraising progress?

Following the seed round, Locus expanded its logistics management platform and raised $2.75M Series A led by Exfinity Venture Partners with Blume Ventures, BeeNext, and Rajesh Ranavat in May 2016, followed by pre‑Series B, Series B, and Series C rounds from investors including Falcon Edge, Tiger Global, GIC, Qualcomm Ventures, and others.

Sources

Funding and outcome facts on this page were researched on 2026-08-22 from the pages below.

Locus.sh (MARA Labs) pitch deck slides

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What each slide of the Locus.sh (MARA Labs) pitch deck says

Slide 1

MARA Labs MARA Ain’t a Routing Algorithm Platform as a Service for Logistics Fulfillment. April 2015 || Nishith Rastogi

Slide 2

Team Nishith Rastogi Geet Garg CEO, CTO Economics + Electronics @BITS-Pilani, Computer Science @IIT KGP, Fraud + ML@Amazon Fraud + ANS@Amazon Linkedin Linkedin Worked for 2 years together at Amazon as engineers, and then built PinChat, a location based chat app. Together, as team we have strong expertise in algorithms and engineering, with past experience in building scalable, externalized, public APIs for Amazon. 2

Slide 3

Expensive pain point in a Massive Market Fast growing need of better tools in delivery dispatch, resource assignment, tracking & route optimization. Solution needed by e-commerce players, Uber for X companies, and any operation with a mobile work force. Inelegant & un-optimized existing solutions. All require massive amounts of manual intervention. Poor end-customer experience A staggering 75% of e-commerce customers feel the need for better tracking. Source 3

Slide 4

Tool for Automated dispatch, tracking & route optimiztion + Eliminate 90% of human intervention in order dispatch, using intelligent algorithms * 75% reduction in effort, when scaling operations to a new city » Exceptional experience to end users with live on-road tracking of order and minute by minute ETA updates

Slide 5

You can't build this in-house while making financial sense = We invest in R&D to create high end algorithms and technology stack to create a robust common Platform = Platform is available as a service to customer at a very affordable pricing, with no operational and maintenance overheads. = Clean APIs allow the solution to be integrated with existing stack, with ease

Slide 6

lllustrative Use Cases Tracking of Goods Propriety Route deviation engine, keeps an eye, and alerts only in case of Dispatch deviations Assignment Provide live update of School Buses, and ETA to bus stop to Schools parents Making station managers obsolete for on-demand delivery. Food-Tech Faster turnaround times, delivers food fresh, and customers see the order reaching them live \ Laundry Pick Up Route Optimization for faster delivery and lower Precise pick-up ETA, costs accounting for live traffic conditions 6 E-Commerce

Slide text above is read directly from the Locus.sh (MARA Labs) deck PDF embedded on this page.

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