Work With Us

🏷 White-Label Platform

Need a community incident-reporting app under your own brand? We license DonzHit.me as a fully rebranded, turnkey solution — your name, colors, and custom event types. The hard infrastructure is already built: GPS ingestion, AI-assisted media review, moderation queues, push notifications, geospatial heatmaps, Cloud CDN edge caching, Cloud Armor WAF, and a real-time public feed.

Ideal for:

• Municipalities & transit authorities
• HOAs & property management companies
• Insurance carriers & fleet operators
• Road safety nonprofits & advocacy groups
• University campuses & sports venues

Two deployment models:

• Multi-tenant (shared infrastructure) — your organization runs under its own namespace on our managed backend. Reports, users, and moderation queues are logically isolated with zero cross-tenant data access. Cost-effective, fastest time to launch.
• Dedicated private instance — your own isolated deployment in your own cloud account: separate backend, database, and storage. Ideal when data sovereignty or regulatory compliance (HIPAA, GDPR, FedRAMP) requires complete physical separation.

💻 Custom Software Development

We design and build production-grade mobile and web applications for organizations that need a community intelligence or reporting layer. Our stack delivers Android, iOS, and web from a single codebase — fast, cost-effective, and maintainable.

Specialties:

• Community-driven incident reporting (traffic, code enforcement, environmental hazards, accessibility barriers)
• Multi-model AI pipelines — LLMs, a physical-reasoning Vision-Language Model, audio-visual fusion, generative video + Text-to-Speech, and chained autonomous agents
• Geospatial dashboards & heatmap analytics
• Backend APIs, cloud infrastructure & DevOps
• Cross-platform Flutter apps & Go services

🔍 Vision-Language AI, Searchable Media & Agents

At the core of DonzHit is a Vision-Language Model post-trained for physical reasoning — it doesn't just label static images, it reasons about motion, physics, and real-world interactions across a clip's frames. In our own testing it correctly identified a vehicle-and-pedestrian impact that general-purpose multimodal models read as a mere "near-miss" — exactly the kind of safety-critical event a generalist model misses.

That model anchors a multimodal fusion pipeline that understands an incident the way a person would — by sight and sound together:

• Sight — the physical-reasoning VLM reads the video frames: who moved where, trajectories, speed, possession, contact, and impact.
• Speech — DonzHit.me's Whisper transcription pipeline captures what was said (a shout, a warning, an exchange); audio is processed entirely within our inference pipeline — no cloud speech API, no third-party service ever receives the audio.
• Sound — an acoustic event detector flags the non-speech audio that transcription can't: the crunch of an impact, a horn, skidding tires, breaking glass, a siren — or an idling vehicle, footsteps, and tearing cardboard.

These signals are timestamp-aligned, so the system correlates the moment a crash is heard with the exact frame it's seen — turning a raw clip into a structured, natural-language account of what was observed. That single understanding then does triple duty:

• Character commentary — it drives DONZ's signature sardonic, on-brand reaction to each approved report. Fully automated, no human in the loop.
• Searchable intelligence — every clip and image is distilled into structured natural language text and markup, unlocking deep content-level search across your entire media archive. Retrieve footage by what actually happens in it — "a cyclist riding on the sidewalk," "an overflowing dumpster behind a building," "a pothole forming at a crosswalk" — not only by timestamp or camera ID. No timeline scrubbing. Months of captured media, queryable in seconds — indexed for sub-second text queries.
• Event-driven agents — when the VLM observes a condition that crosses a rule you define, an autonomous agent fires: open a work order, route a ticket, alert a supervisor, escalate to a dashboard, or call into an existing system via webhook or API. Each agent is configurable as human-in-the-loop or fully autonomous.

In practice: a resident photographs an overflowing bin → the VLM reads the scene → an agent opens a sanitation work order and notifies the route supervisor — before anyone in the office has seen the photo.

🛡 Security-First Engineering

Security is designed in from the start — not bolted on after the fact. Every layer of our stack is hardened against modern threats.

• CVE tracking & dependency auditing — continuous scanning against known vulnerabilities before every deploy
• OWASP Top 10 hardening — injection prevention, XSS sanitization, broken access control, and insecure deserialization addressed at the framework level
• Device-lock gate for admin — opening the admin console on mobile requires biometric (Face / fingerprint) or PIN every time; a device with no lock set cannot open admin at all. On web, admin entry is TOTP-gated and strictly view-only
• Hardware-attested zero-trust mobile authentication — Firebase App Check binds every API request to a verified, unmodified app install on a genuine device, backed by Play Integrity (Android) or App Attest / Secure Enclave (iOS). Combined with role-stratified short-lived JWTs, TOTP per-session challenges, and configurable per-TOTP transaction caps, this forms a layered zero-trust authentication stack that remains secure even when individual credentials are exposed
• TOTP authentication — all privileged admin operations require a live TOTP challenge in addition to JWT-based access, eliminating credential-only attack surfaces
• Rate limiting, Cloud WAF & CDN edge caching — IP-level token-bucket throttling, Cloud Armor WAF (OWASP rule sets: XSS, SQLi, RFI, LFI, scanner blocking), DDoS protection at the edge, and Cloud CDN that absorbs ~95% of public feed traffic before it ever reaches the origin — sub-millisecond delivery and near-zero Firestore load during traffic spikes
• Immutable audit trails — every privileged action is written to an append-only log for compliance, forensic traceability, and incident response
• Zero-trust service architecture — services authenticate with short-lived identity tokens; no service is implicitly trusted by network proximity alone

⚙️ AI-Powered Admin & Operations

Managing a live community platform at scale demands more than a settings panel. Our operator layer is a full command-and-control environment backed by autonomous AI agents and a real-time event pipeline.

Access is governed by a three-tier role system — super admins, admins, and moderators — with granular per-permission flags for every sensitive operation. All sensitive actions require a live TOTP challenge and are written to an immutable audit trail.

Multi-tenant aware throughout — operator panels, moderation queues, and user roles are all scoped to the organization, ready to serve multiple licensed deployments from one backend.

🔍 Click to expand

📊 Data & Analytics Partnerships

The anonymized, location-tagged incident data generated on our platform has value well beyond individual reports. We're open to discussions with traffic safety researchers, urban planners, insurance actuaries, and policy advocates about:

• Structured data feeds & licensing agreements
• Joint research and publication
• Integration with existing city or agency data systems
• Custom analytics dashboards for your organization

🥽 XR Integration — Extended Reality & Smart Glasses

DonzHit.me is in active development of an XR Emulator and a purpose-built DonzHit XR app designed to run natively on extended-reality hardware. The architecture is built to integrate immediately and directly with any XR smart-glasses platform upon release — including Google's forthcoming Android XR glasses — without a re-build or re-architecture.

What this opens up:

• Hands-free incident capture — a field officer, safety inspector, or community member sees and records simultaneously, without reaching for a phone
• Real-time DONZ AI overlay — the VLM analysis and DONZ reaction surface as a heads-up display annotation as the clip is reviewed, not after
• Spatial incident mapping — GPS-tagged reports anchored to the physical world, visible as AR pins in the user's field of view
• Emulator-first development — our XR Emulator lets partners prototype custom XR workflows and UI overlays before hardware is available, so integration work starts now

If your organization is planning for an XR-enabled workforce — public safety, infrastructure inspection, fleet management, or campus security — we are the right partner to build on.

💜 Nonprofit & Municipal Programs

Safer streets shouldn't require a large technology budget. We offer discounted licensing and pro-bono consulting for qualifying nonprofits and under-resourced municipalities focused on road safety, pedestrian advocacy, micromobility programs, or community watch initiatives.

If your mission aligns with ours — making public spaces safer for everyone — let's talk.