SafeGuard: Auto SOS SMS+Call

I provide an Android on-device Auto-SOS engine designed to address the most common real-world failure point of emergency systems: when the person involved cannot operate the phone, the workflow can still continue automatically. It runs entirely on-device and does not rely on cloud accounts or tracking dashboards. After a trigger, it starts a countdown confirmation; if there is no response, it automatically escalates by notifying a predefined trusted contact chain via SMS, phone call, and last known location—reducing the “Silent Gap” between an incident and when others become aware.

The product is already live on Google Play as a fully functioning Android app.
I am seeing organic installs from users who actively search for safety / SOS tools, and there are already paying subscribers on the current subscription model.
The app is stable in production, runs fully offline on-device, and I am now focusing on improving retention, fine-tuning detection logic, and preparing localization for more markets.

Safety and security product teams that need an on-device escalation layer for incidents where the user cannot operate the phone.

Hardware and device ecosystem players with Android apps (wearables, rugged devices, health/senior care devices) that want a turnkey Auto-SOS capability.

Carriers, insurers, and assistance/service providers seeking a differentiated safety feature without building a full cloud tracking stack.

Integrators, resellers, and agencies that can package and resell the capability to enterprise or consumer channels.

Market:
The market spans mobile safety, personal emergency response, connected devices, and assistance services. Initial focus is on Android-centric deployments where on-device execution is a priority and cloud dependency is undesirable; the asset can be licensed, integrated, and commercialized across multiple verticals and geographies.

In many real-world incidents, people do not die instantly from the accident itself, but because nobody notices for hours.
Falls at home, car crashes on empty roads, sudden medical events, or attacks by abusive partners often leave the victim unable to operate their phone.
Most existing SOS tools assume the user can unlock the phone, find a button, or speak. In the critical minutes when people are unconscious, frozen, or physically unable to move, these tools fail.
The opportunity is to build a “safety base layer” that works exactly in those moments when the user cannot help themselves.

Please confirm whether you are willing to proceed to an NDA for technical and asset review (source code, workflow documentation, and test/integration materials). I’m flexible on the deal structure based on the buyer’s preference: a full buyout or licensing (including reseller/agency arrangements or secondary integration for resale) are all acceptable. Please share your preferred path and target timeline so I can provide the corresponding materials and a terms framework to accelerate the transaction and commercialization.

Existing alternatives include:
• Built-in SOS functions on smartphones (e.g. side-button presses, manual emergency calls).
• Cloud-based safety apps that require an internet connection and accounts, often focused on tracking or check-in flows.
• Wearables with fall detection or panic buttons.

All of these share one core limitation: they still assume the user can press a button, unlock a screen, or speak at the critical moment. Many also depend on cloud services, continuous connectivity, and centralized dashboards, which raises privacy concerns and can fail exactly when networks are unstable.

Advantages and Differentiators

Targets the most common real-world failure point: Most SOS solutions assume the user can operate the phone. This engine is designed so the workflow can continue even when the user is incapacitated or unable to interact.

On-device execution with minimal cloud dependency: It does not require cloud accounts or tracking dashboards to run the core escalation flow, reducing deployment friction and privacy risk.

Actionable escalation chain: After a trigger, it can run a countdown confirmation; if there is no response, it escalates via SMS + phone call + last-known location to a predefined trusted contact chain, enabling immediate action by recipients.

OEM-ready integration / commercialization-friendly delivery: It can be delivered as a transferable asset package (source code + workflow documentation + test/integration materials) so a buyer can integrate it into existing products and commercialize quickly.

Verifiable and traceable engineering: Includes local event logging and supporting test/integration materials to facilitate validation, debugging, and ongoing maintenance.

Revenue Streams

At present, revenue primarily comes from app subscriptions. In addition, if a third party acquires or takes over this capability, they can generate revenue through resale, licensing, reseller/agency distribution, or secondary integration and commercialization via their own channels and customer base.

Cost Structure

At this stage, I am a solo developer, and the main cost is marketing and advertising spend. Other operating costs (e.g., staffing, servers) are largely negligible because the core system runs on-device and does not rely on cloud accounts or tracking dashboards.

Business Model

I am focused on an asset sale (buyout): selling an Android on-device Auto-SOS engine (on-device safety escalation/notification capability) together with a complete deliverable package (source code, workflow documentation, and test/integration materials). A non-confidential teaser is available for quick screening prior to an NDA; under NDA, full technical and asset review is available to move toward closing. The transaction can be structured as a one-time buyout, optionally with milestone-based acceptance payments to accelerate execution.

Channels

Primary channels are direct outreach to buyers and intermediaries: email-based outreach, M&A/licensing advisors, and resellers/agents who can source strategic buyers. I share a forwardable teaser for initial qualification; once there is interest, we proceed to NDA, technical review, and term negotiation. I may also post the teaser publicly to capture inbound buyer leads (positioned explicitly as a buyout opportunity).

Metrics

Success is measured through a deal pipeline funnel: qualified leads, teaser reply rate, NDAs signed, technical review completion, number of term sheets/offers, and ultimately deal value and time-to-close. Secondary metrics include weekly lead volume, conversion rates by channel, and speed of progression (first contact → NDA, NDA → offer/LOI).

The funds will mainly be used to:
• Continuously strengthen existing guard modes: Improve the detection logic and stability of the current accident guard (speed + G-force), long inactivity guard, abnormal-location stay guard, and heart-rate guard, in order to reduce both false positives and false negatives.
• Complete the planned new guard modes: Develop the next wave of guard modes already on the roadmap, such as water / drowning risk, abnormal environmental audio, and suspected “not operated by the owner” behaviour, to make the overall protection system more complete.
• Run targeted marketing and ad experiments: Conduct small but focused marketing and advertising tests to identify the most effective channels to reach the right users and payers.
• Purchase and test a wide range of devices: Buy and test different Android phone models and multiple heart-rate wearables to validate compatibility and stability across real-world hardware.
• Cover essential operating costs: Support ongoing development, maintenance, and user support so that the core safety features can remain affordable for people who need them.

I am looking for partners who genuinely understand the “late discovery” problem and are willing to support the development of an offline auto-SOS safety layer over the long term — not just investors chasing the next hype app.

At the pre-seed stage, I am open to discussing a fair equity stake in exchange for funding. The priority is not maximizing valuation, but securing several years of stable runway so that this system can be built correctly, made robust, and kept running.

From a market perspective, any smartphone can potentially become a SafeGuard device — this is a space measured in billions of phones worldwide. But my ultimate goal is not just revenue growth. Once operations reach a certain scale, I want to be able to reduce or waive fees for some high-risk, vulnerable, or low-income users, so that automatic SOS can become an affordable safety layer rather than a luxury.

If an investor cares about reputation and real-world impact, and wants their capital to contribute to something tangible in human safety, this is a very suitable problem space.
For me personally, the main question is not “how much can this be worth,” but whether this system can keep running, reach more people, and quietly prevent deaths that would otherwise happen simply because nobody realized in time.

Integration scope and acceptance criteria: The main risk is alignment on the buyer’s intended integration form and support scope (SDK / system service / reference app). This is controllable by defining a clear deliverables list and acceptance criteria upfront.

Handover and knowledge transfer: Fast deployment depends on sufficient documentation and key design context. This can be mitigated through NDA-based technical review and a fixed handover/support period (optional).

IP and licensing definition: A one-time clarification in the agreement of IP transfer/licensing scope, exclusivity, resale/sublicensing rights, and territory/product-line boundaries minimizes the risk of future disputes.

I have not yet participated in any formal incubation or acceleration programs. My main focus so far has been on building the product and validating it with real users.

I have not yet entered related competitions or received awards, as I am currently prioritizing product execution and real-world user validation.