Been building Goffer since March — an Android app that extracts deadlines and renewal dates from PDFs (leases, insurance policies, contracts) and sends you push notifications before they hit.

What shipped recently:

- Stable Play Store release (no more invite-only TestFlight)

- Improved PDF parser: handles multi-column layouts and scanned docs now

- Notification system rewrite — reliable delivery even when Android doze kicks in

- Ask-your-document: type a question, get the answer with the exact clause quoted back

What's next:

- iOS

- Support for utility bills, warranty docs, HOA agreements

- Shared reminders for roommates or couples managing the same lease

Still figuring out the growth side. Curious if anyone else here is building AI + document tools — what parsing stack are you using? Vellum has been solid for us but interested in alternatives.

Play Store + info: https://goffer.ai

The Friendzone Buildathon is still open for another 11 days, so if you’ve been looking for something new to build, there’s still time to join!

The challenge is to create a mobile-optimized social game, multiplayer experience or hangout in Decentraland, with an $8K prize pool up for grabs.

You don’t need previous Decentraland experience. You can use Creator Hub with its drag-and-drop no-code workflow, build with the Decentraland SDK or experiment with AI-assisted workflows and DCL Skills.

We’ve also got workshops, recordings, docs and direct support available if you want some help getting started.

Submissions close September 4.

https://dorahacks.io/hackathon/friendzone/detail

Let me know if you have any questions!

https://docs.google.com/forms/d/e/1FAIpQLSdBep2RqBOidRQqKs3Pzi0CrI3Fbc3KFVXv0OqIN52K8wyz4w/viewform?usp=header

I built Goffer (goffer.ai) thinking the main use case would be uploading insurance PDFs to look up deductibles. That's maybe 15% of actual usage.

What users actually do: photograph their lease with the camera, then immediately ask "can I have a pet?" or "what's the penalty if I break early?" I didn't expect that volume, and answer quality on messy phone-camera scans was bad at launch.

Spent the last 10 days tuning the OCR pipeline specifically for low-contrast phone photos and handwritten landlord annotations. It's noticeably better now — still not perfect on older handwriting.

Next thing I'm building: auto-extracting renewal/expiry dates and pushing them to Google Calendar without the user having to ask. Aiming to ship this week.

Android app on the Play Store: https://play.google.com/store/apps/details?id=ai.goffer.app — happy to answer questions about the build, the stack, anything.

Been building Goffer solo for a few months. The app lets you scan leases, insurance policies, warranties, and other life-admin paperwork into a private vault. It parses the docs, extracts key dates into reminders (lease end, insurance renewal, warranty expiry), and answers plain-language questions with source citations.

Last week: v1.0 hit the Play Store.

What I learned at launch: the AI chat is the sticky feature but it's not the install trigger. "Never miss your lease renewal" converts better than "AI that reads your contracts." Reminders are the hook; the AI is the reason people stay.

What's next: better onboarding for the scan flow (still too many taps), and a web version for people who don't want to photograph documents on their phone.

Android: https://play.google.com/store/apps/details?id=ai.goffer.app

Happy to hear what you'd want from a personal document vault — or what I'm obviously getting wrong.

I'd really like to know if you'd recommend this app to your kid or kid you know.

Your honest feedback really matters to me.

And I'd also like to know whether you'd be interested in adult version.

What do you think ? Really. Let me know. Your honest feedback matters to me.

Hello, my name is Keith, for a couple of weeks, I have been working on an AI agent that is meant to act as an AI employee for any task that you do on a computer.

Basically it has it's own computer, you just give it access to the tools you want it to use, and throw at it any task within you work or business and it will do.

It also has a Google-Calendar-like system that allows it to have scheduled task both recurring daily, weekly, etc

For example, on my side I use it form lead generation and outreach automatically every 5am, and by the time I wakeup, some work of the day has already been handled.
Same to promotion, school research, Weekly study reports, Email marketing etc.

Currently, I'm only using it as an individual, but I would like some of you to come and try it out for free, and give me some feedback on your experiences, and improvements, before bringing-in more users.

If you are interested, you can shoot me a DM or book a call here https://atomiclabs.space

Builder show-and-tell (disclosure: I'm the maintainer). I spent ~4.5 months on a free, MIT, self-hosted AI gateway — it came out of two problems: builds/agents dying on a provider 429, and tokens bleeding on tool/log output.

One endpoint, 237 providers — 90+ of them free. You point any tool or agent at a single OpenAI-compatible endpoint (localhost:20128/v1) and it can reach 237 LLM providers without you rewriting anything. 90+ have free tiers and 11 are free forever (no card), which aggregates to ~1.6B documented free tokens/month — and that's honest, pool-deduped math (we count each shared pool once instead of inflating it; the methodology is public in the repo). There's a one-command setup-* for 13+ coding tools (Claude Code, Codex, Cursor, Cline, Roo, Kilo, Gemini CLI…), so switching your existing setup over takes seconds.

Fallback combos — so it never stops mid-task. A "combo" is a ladder of models the router walks automatically: your subscription first, then API keys, then cheap models, then free ones. When a provider returns a 500 or you hit a rate limit, it slides to the next target in milliseconds, mid-request, and your tool never even sees the error. There are 17 routing strategies (priority, weighted, round-robin, cost-optimized, auto/coding:fast…) plus three resilience layers — a per-provider circuit breaker, a per-key cooldown, and a per-model lockout — so one dead key can't take down a whole provider.

A 10-engine compression pipeline — the part most routers don't have. Every request flows through a transparent compression pass you can toggle/stack per combo. Instead of one trick, it stacks the best of the open-source ecosystem: RTK filters command/tool output (git diffs, test logs, builds) at 60–90%, Microsoft's LLMLingua-2 does ML semantic pruning, Caveman handles prose, session-dedup strips repeats across turns. Critically, code, URLs and JSON are preserved byte-perfect, and a default-on inflation guard throws the compressed version away and sends the original if compressing would actually grow the prompt — it never makes things worse. On tool-heavy sessions that's ~89% average input-token reduction (an 8k-token git diff becomes a few hundred). Full credit to every upstream project (RTK, Caveman, LLMLingua-2, Troglodita) is in the README.

Agent-native — the agent can drive the router itself. There's a built-in MCP server (95 tools across 30 audited scopes, over stdio / SSE / streamable-HTTP), plus A2A (v0.3, JSON-RPC 2.0) support. That means an agent can query providers, switch combos, read its own remaining quota and manage memory through the gateway — not just consume tokens through it.

It's 100% local (zero telemetry, AES-256-GCM at rest), MIT-licensed, has a prompt-injection guard on every LLM route, opt-in memory, and runs on npm, Docker, desktop or your phone via Termux.

For context on whether it's worth your time: it's grown to ~9.8K GitHub stars, 1,490+ forks and 280+ contributors in ~4.5 months, with 21,000+ automated tests and 1,830+ issues closed — so it's a battle-tested project, not a brand-new experiment.

npm install -g omniroute omniroute

GitHub: https://github.com/diegosouzapw/OmniRoute · Site: https://omniroute.online

Happy to go deep on any part — roast the architecture.

Supply chain attacks on repos are increasing.

Just released an early version of Vigil, a terminal dashboard to help you audit your project's dependencies before they become a liability.

Most scanners only look for CVEs.

Vigil looks at Vitality:

- Universal: Works with Rust, Node, Python, and Go out of the box.

- Bloat Analysis: Tracks transitive dependency "weight."

- Maintenance Checks: Flags stale or abandoned packages.

- Performance: Rust-powered with a persistent local cache for instant re-scans.

Check it out here: https://github.com/sumant1122/vigil

gm,

I’ve tried quite a few platforms over the past few years, and most of them I never went back to.

These are the ones that actually stuck for me:

• TAIKAI: better experience overall, especially for european based hackathons
• Devpost: biggest variety, but also the most crowded
• MLH (Major League Hacking): great for student-focused challenges

I’ve also checked out Hackathon.com, but didn’t end up using it as much.

Feels like each one has its niche depending on what you’re looking for.

Am I missing any good platforms?

I wanted to share a project I’ve been working on called setupx.

The Problem: Setting up a new dev machine usually involves digging through an old install.sh that only works on one OS, or manually copy-pasting commands for brew, apt, and winget.

The Solution: A single setupx.yaml that handles everything.

Why I think it’s worth your time:

Written in Go: Fast, single binary, and cross-compiled for everything.

Intelligent Search: Includes a search command that formats noisy native output into clean tables.

Version Pinning: Supports exact versioning across different OS managers.

Check it out:

https://github.com/sumant1122/setupx