HomeSafe

public records about Boston homes, remembered for the people who live in them.

HomeSafe pairs the city’s own data with a renter’s private, dated journal and an agent that answers questions with receipts: every claim cites a source it actually read, and anything it can’t prove gets deleted before you see it.

A long row of brick apartment buildings with bay windows and window air conditioners in Boston
The housing stock the records describe: triple-deckers and multi-family homes. Photo: Brett Wharton, Unsplash.

Look up any Boston address, right now

Violations, permits, and housing complaints, each labeled with how confidently it was matched, and what it does not prove. A permit is never presented as a repair.

How it helps a renter hold a landlord accountable

A journal that stands up

Dated, private notes. Photos are described by you, never analyzed by the AI, and location data is stripped before an image leaves your phone.

Your building’s paper trail

One real six-unit building in Roxbury carries 53 heat complaints and one permit. One complaint is a story; fifty-three is a pattern an inspector can act on.

Answers with receipts

The agent reads your notes, the city’s records, and the Massachusetts sanitary code, and shows exactly what it read. If it cannot cite a claim, it deletes the claim and tells you it did.

The hackathon criteria, exceeded

Every row is verifiable in the repo: tests, evidence files, and decision docs are linked from the README.
CriterionRequiredWhat HomeSafe ships
CockroachDB toolsat least 2All 4: distributed vector indexing (1024-dim, consent-filtered), managed MCP at build time with findings filed as feedback, ccloud for the two-login security model, and the Agent Skills repo doing load-bearing privilege work.
AWS servicesat least 13: Bedrock (agent + embeddings via a role that can invoke exactly two models, no keys in the build), Amplify Hosting, S3.
Store, retrieve, act on memorythe challengeAll three verbs, live: the agent writes its own conclusions back to memory, recalls them next session by meaning, and drafts approval-gated tasks. Six kinds of memory in one cluster: records, journal, vectors, agent diary, task state, audit log.
Memory not an afterthoughtthe judging barMemory that proves itself: every answer ships a receipt of what was read, written by the retrieval layer. The model cannot author it. The receipt is also the audit row and the validator’s source of truth.
Production readinesssecure, resilientPrivacy by missing GRANT, prompt injection tested live (nothing leaked; the withheld count moved), notes survive model outages, revoked memory erased by the database’s own row-level TTL, follower reads on the million-row timeline.
Real-world impactmeaningful use caseBoston renters vs. undocumented housing conditions, with the entire Massachusetts sanitary code retrievable by meaning and cited to the section, plus referrals to legal-aid guides.

191

tests passing, several against the live cluster and real model calls

138–155 ms

consent-filtered vector search over seeded memories

87

Massachusetts housing rules in memory, each linked to its source

0

private items leaked under live prompt-injection attack

See the receipt for yourself

Sign in with just a name, open a case, ask a question. Then open “Why do I remember this?” and read exactly what the agent read.

Open the live demo