QerisAI Trust Infrastructure · Founder Project
Qeris
Founded and built Qeris, a trust intelligence platform that evaluates digital content and links through structured signals, risk analysis, confidence scoring, and explainable trust decisions.
Quick facts
- Role
- Founder & Product Lead
- Status
- Public alpha · Production infrastructure active
Overview
Qeris is a trust intelligence platform designed to help users, developers, and digital platforms assess whether online content, links, and interactions can be trusted. The product combines structured signal collection, deterministic evaluation, risk analysis, confidence scoring, and explainable decisions through a production Core Service and browser experience.
Problem
What the work needed to resolve.
Online users increasingly encounter malicious links, impersonation, manipulated content, misleading information, and uncertain digital authenticity across social platforms, messaging products, and the wider web. Qeris was designed to create a reusable trust layer capable of turning multiple verification signals into understandable decisions for users and software systems.
Approach
From definition to delivery
- Designed Qeris as infrastructure rather than a single-purpose content scanner
- Created a modular signal-provider model so independent verification sources can contribute structured evidence
- Built a Trust Engine that aggregates signals into risk, confidence, verdicts, reasons, and diagnostics
- Connected a browser extension to the production Core Service for real-time remote evaluation
- Designed the platform for future API, SDK, browser, platform, and security-team integrations
Architecture
Product structure and system design
- Signal Framework — provider contracts, collection, validation, catalog governance, and conformance testing for structured trust inputs
- Trust Engine — weighted aggregation, critical overrides, deduplication, conflict detection, deterministic decision IDs, and reason codes
- Decision Schema — structured verdict, risk, confidence, reasons, timing, policy, evidence, and diagnostics
- Core Service — production evaluation API, authentication, scoped key access, metadata, key introspection, and revocation controls
- Browser Extension — remote evaluation experience presenting trust score, confidence, risk, reasons, evidence sources, findings, and recommended action
- Integration Layer — shared packages, SDK foundations, and interfaces designed for future developer and platform integrations
Technical Highlights
Built and validated components
- Built as a TypeScript monorepo with shared primitives, signal framework, Trust SDK, integration, Trust Engine, and guidance packages
- Implemented deterministic trust evaluation with weighted signal aggregation and critical-risk override logic
- Added provider conformance tooling, signal catalog governance, validation fixtures, and automated tests
- Deployed the Qeris Core Service to production infrastructure
- Implemented SHA-256 hashed API secrets with scopes, metadata, last-used tracking, introspection, and revocation support
- Packaged a production browser extension that operates in remote-only mode against the Core Service
- Built user-facing diagnostics covering trust decision, score, confidence, risk, summary, reasons, evidence sources, detailed findings, and recommended action
- Validated production decisions against normal domains and a known malware test URL
Execution
Responsibilities and delivery
- 01Product vision, positioning, and roadmap
- 02Trust architecture and system boundaries
- 03Signal Framework direction
- 04Trust Engine requirements and decision logic
- 05Browser extension product direction
- 06Core Service production requirements
- 07API key and access-control requirements
- 08Product QA and production validation
- 09Technical documentation and architecture decisions
- 10Public product positioning and website direction
Decisions
Choices that shaped the work
Infrastructure-first product architecture instead of a manual scanner
Explainable trust decisions instead of opaque scoring
Provider-based signal architecture to support multiple verification sources
Deterministic Trust Engine behavior for predictable evaluation
Remote-only production extension mode to keep evaluation logic in the Core Service
Scoped and revocable API credentials for production access
Developer API and integration direction alongside the consumer browser experience
Approved evidence
Collaborative scale and outcomes
- Production Core Service is active
- Browser extension has been packaged for public-alpha use
- Production extension is configured for remote evaluation
- Safe-domain evaluation returned TRUST with low risk
- Known malware test evaluation returned DO NOT TRUST with critical risk
- Core packages have passed typechecking, builds, and automated test suites during stabilization
Outcome
Built and stabilized a public-alpha foundation consisting of a production Core Service, packaged browser extension, modular signal framework, deterministic Trust Engine, scoped API-key controls, explainable decision UX, and working remote trust evaluation.
External links
