Zaya (Internal) - Web App + Desktop Agent + Chrome Extension
An internal recruiting productivity platform built as a three-part system: Web App (command center), Desktop Agent (orchestration + co-pilot), and Chrome Extension (in-context workflows).
TL;DR
- What it is: An internal recruiting productivity platform built as a three-part system: Web App (command center), Desktop Agent (orchestration + co-pilot), and Chrome Extension (in-context workflows).
- Primary objective: Improve both speed and quality of recruiter workflows.
- Core use cases: Better profile discovery from job boards (e.g., Naukri), AI-assisted shortlisting, and workflow improvements across sourcing → screening → outreach. (Internal-only; metrics omitted; currently in development.)
Context
Recruiters lose time and quality when workflows are fragmented: sourcing and screening happen across multiple tabs/tools, shortlisting depends heavily on manual judgment at speed, and outreach and follow-ups are repetitive and inconsistent.
Zaya was built to make recruiting workflows faster, more consistent, and easier to operate, while adding AI assistance in a controlled way.
Scope: Zaya is internal-only and currently in development. This page focuses on the system design and workflow intent, without exposing sensitive data, internal performance numbers, or proprietary implementation details.
What the product does
- Central place to manage workflows, views, and operational dashboards
- Configuration surface for templates, rules, and reporting views
- Provides a single hub for recruiter productivity signals
- Built using Electron
- Hosts the primary "co-pilot" intelligence layer and orchestrates actions across components
- Coordinates tasks that need reliable execution across the recruiter's environment
- Enables actions inside the browser where recruiters already work
- Captures context and reduces manual copy/paste
- Triggers co-pilot and workflow steps without forcing a tool switch
- Streamlines discovery and capture of better-fit profiles from job boards (e.g., Naukri)
- Makes profile intake more structured and consistent
- Uses AI assistance to improve shortlisting and reduce noise
- Supports faster "qualify vs. disqualify" decisions with recruiter-in-control design
- Reduces repetitive steps across sourcing, screening, and outreach
- Uses templates and structured capture to make execution consistent across recruiters
- Integrates with email workflows for outreach and follow-ups (vendor-agnostic)
Feature highlights
- Web hub to manage workflow views and recruiter activity
- Browser extension to capture profiles and trigger actions in-context
- Desktop co-pilot to assist with screening/shortlisting workflows
- Structured notes and templates to standardize evaluation
- Human-in-the-loop co-pilot (suggestions support decisions; recruiters remain accountable)
- Role-based boundaries and controlled access to internal workflows
- Audit-friendly workflow traces (what happened, when, by whom)
- Instrumentation for adoption and workflow bottlenecks (internal reporting)
Key decisions
Tradeoff: simpler build vs deeper workflow integration. Chose Web App + Electron Desktop Agent + Chrome Extension to meet recruiters inside their daily tools while keeping a central control plane.
Tradeoff: optimize only shortlisting vs improve upstream inputs. Focused on getting better profiles from job boards and standardizing how profiles are captured and evaluated.
Tradeoff: maximum automation vs trust and control. Chose co-pilot design that supports shortlisting decisions while keeping the recruiter in control and enabling traceability.
Impact
Technical depth
- Defined responsibilities across web app, extension, and Electron desktop agent
- Designed workflows for reliability (coordination, fallbacks, clear handoffs)
- Built a co-pilot architecture that supports human-in-the-loop decisioning
- Integrated with job board and email workflows in a vendor-agnostic way (no sensitive details)
Collaboration
- Engineering (architecture, reliability, integration boundaries)
- Design (workflow ergonomics, low-friction UI, cognitive load reduction)
- Recruiting teams (shadowing, feedback loops, iteration)
- IT/Security stakeholders (internal constraints and deployment expectations)
Testimonial
“The co-pilot suggestions helped our recruiters find qualified candidates faster while keeping control and context.”