Doorstep.ai

Name: Doorstep.ai
Brand: Doorstep

AI Native

bring indoor visibility to your delivery tracking.

Est 2023|Valuation $26M|Raised $8.1M

LinkedIn 1K|Website|Web traffic 16K|FTEs 16|HQ New York, New York, US

MarketsSupply Chain Visibility

Published Jul 14, 2026

01Common complaints

- Organizations that require a full last-mile platform (routing, dispatch, customer communications) rather than an SDK-based signal layer; platforms such as Onfleet, Bringg, or Descartes may be more appropriate for full operational replacement. - Organizations that require publicly documented certifications (SOC 2 / ISO 27001) prior to engagement; Doorstep does not publicly publish these certifications in the reviewed sources. - Delivery operations where drivers use BYOD policies with limited app permissions or where operating-system background-sensing constraints would prevent expected SDK behavior. - Use cases where the root cause of disputes is unrelated to indoor ambiguity (for example, porch theft, incorrect item selection, or merchant errors) and where indoor path tracking would not address the primary issue. - Budget or procurement situations where the lack of transparent pricing and public case studies makes it difficult to justify a pilot in comparison to lower-risk alternatives (improved photo POD, enhanced customer communications, locker solutions, etc.).

Disqualifying criteria (poor fit)

No control over the driver app (for example, reliance on third-party driver apps)
Delivery footprint is predominantly low-density, single-family suburban deliveries where indoor ambiguity is less common
Procurement policies that require publicly documented security certifications (e.g., SOC 2, ISO 27001) before pilot approval

Publicly acknowledged limitations

Doorstep’s public materials do not provide a comprehensive list of known limitations.

Practical limitations and risk areas (based on product type and public disclosures)

Accuracy variance depending on device sensor quality and building structure.
Potential impact from OS-level permission and policy changes that affect background motion or location sensing on iOS and Android.
Lack of publicly documented security certifications may slow enterprise adoption.
Limited public references and reviews create uncertainty around support quality, implementation timelines, and real-world ROI.

SDK ecosystem signals

Doorstep provides documentation and packages for multiple stacks (React Native, Flutter, native mobile). Maven repository listings show frequent version releases in 2025 for the Android artifact, indicating active development, but public artifact pages do not provide detailed change logs or operational guidance beyond packaging metadata.

02Why they buy

Differentiators (as described by Doorstep)

The company states the SDK is capable of detecting indoor events in GPS-degraded environments using on-device sensor fusion.
The SDK is described as able to infer building entry, elevator/stairs usage, floor reached, and drop-off events.
The approach is software-only and does not require additional hardware.

Evidence quality

Most claims about these differentiators are vendor-published (website, press releases, investor materials). Independent user validation through review platforms or detailed public case studies was limited in the sources reviewed.

Where competitors may have an advantage

Onfleet, Bringg, and Descartes: broader feature sets, established operational tooling, and more documented enterprise procurement footprints.
Zebra-centric ecosystems: established hardware and workflow guarantees for explicit POD capture.

03Field reports

Review-platform presence (G2 / TrustRadius / Gartner Peer Insights)

G2: No Doorstep.ai product listing or reviews were found in the accessible sources during this research.
TrustRadius: No Doorstep.ai product listing or reviews found in accessible sources.
Gartner Peer Insights: No accessible Doorstep.ai listing or reviews found.

Note: Some review platforms restrict crawling. Even accounting for that, Doorstep appears to have limited presence on mainstream review sites at the time of research.

Community / social discussions (Reddit, Hacker News)

Reddit: Searches for "doorstep.ai" predominantly returned unrelated threads or general discussions rather than substantive user reviews of Doorstep.ai’s SDK. No first-person implementation experiences were located in accessible results.
Hacker News (news.ycombinator.com): No specific discussion thread about Doorstep.ai was located in accessible results.

What customers cite as the rationale (inferred from vendor materials)

From the website and press materials:

Reduce "delivered but not received" disputes; improve refund accuracy and customer support outcomes.
Provide indoor context beyond GPS and standard POD photos.
Avoid additional hardware by using a software-only SDK approach.

Common complaints (what’s missing)

Because independent user reviews are scarce, this section is based on gaps in public documentation and typical risks for SDK-based sensing systems:

Lack of publicly documented security certifications and limited pricing transparency.
Risks typical of sensor-based mobile SDKs: battery/performance variability and potential false positives.

Public case studies

No detailed public customer case studies with named customers, before/after metrics, or implementation timelines were found in the reviewed sources.

Vendor-published ROI/fraud numbers (critical view)

A press release includes broader industry and ROI-related statements such as the proportion of consumer fraud attributed to false refunds and typical costs of failed deliveries, but these figures are presented without disclosed methodologies in the release and are not independently validated in the materials reviewed.

04Best fit

Company sizes

Best fit: midmarket-to-enterprise delivery platforms (organizations of substantial size with in-house engineering resources capable of integrating an SDK and running pilots).
Potential fit: larger retailers or 3PLs that operate a dedicated driver app and have significant urban delivery volume.

Industries / verticals

Food delivery marketplaces
Parcel and package delivery
Retail last-mile delivery
Potentially higher-value regulated deliveries (for example, healthcare) if compliance and security requirements can be satisfied

Roles / personas

VP / Head of Last-Mile Operations
Fraud, Trust & Safety, and Risk teams managing refund/dispute economics
Customer Support Operations leaders
Mobile engineering leads responsible for SDK integration
Data/analytics teams responsible for event-stream integration

Key pain points addressed

"Delivered but not received" disputes in multi-unit buildings
Costs associated with refunds and reships
Limited utility of GPS and standard POD photos for indoor delivery context

Qualification criteria (strong fit)

High concentration of multi-unit/apartment deliveries
Clear economic impact from disputes and refunds
Control over the driver app and the ability to instrument events

05The pitch

What the product does (core value proposition)

Doorstep.ai provides an SDK that last-mile delivery platforms embed into their existing driver app to capture granular indoor delivery journey events (for example: parking, building entry, elevator/stairs, floor reached, and final drop-off). The company uses the term "proof of doorstep" to describe this capability, which is intended to provide additional delivery verification and reduce disputes/refunds in multi-unit buildings where GPS and standard proof-of-delivery photos may be insufficient. On its website, Doorstep states its SDK uses "patent-pending sensor fusion" on drivers' smartphones to detect indoor events in GPS-degraded environments, with limited battery impact and broad device support (including specialized handhelds such as the Zebra TC-77). The integration model described in documentation consists of basic integration steps: initialize the SDK, start tracking, mark delivery events, and stop tracking.

Target market and positioning

- Primary buyers: on-demand delivery platforms, carriers, and logistics operators that operate their own driver apps or can modify them. - Primary use cases: dense urban delivery, multi-floor residential buildings, "delivered but not received"/refund disputes, and costly re-ships/reships. - Positioning: positioned as an additional data layer for drop-off verification rather than a full routing/dispatch system—designed to integrate with existing delivery stacks.

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