OVI is the AI-native ATS where you chat to hire. Two AI agents — Sora for sourcing and Milo for screening — find candidates, score every CV, and run AI interviews, all controlled from a single chat.

What does "chat to hire" mean?

Chat to hire is OVI's AI-native hiring workflow: instead of clicking through a traditional ATS, you describe what you need in chat and OVI's AI agents source candidates, screen applicants, run AI interviews, and send outreach for you.

What is an AI-native ATS?

An AI-native ATS is an applicant tracking system built around AI agents rather than forms and pipelines. OVI's AI chat ATS lets recruiters source, screen, interview, and follow up through conversation — the agents do the work and surface only the candidates worth meeting.

Who are Sora and Milo?

Sora is OVI's AI sourcing agent — she scans LinkedIn, the open web, and your ATS history to find best-fit candidates and reach out in your name. Milo is OVI's AI screening agent — he scores every applicant against your rubric and surfaces a ranked shortlist.

How do OVI's AI interviews work?

OVI runs async AI interviews for every shortlisted candidate and returns scores, transcripts, and recordings — so your team only meets the people worth meeting.

Phenom Launches WorkOps: A 6-Layer AI Architecture That Redesigns How HR Work Gets Done

2026-06-19

Enterprise HR technology is in the middle of a confidence crisis. Phenom, the talent experience platform, is making a direct bid to fix it.

At IAMPHENOM 2026 (March 10–12, Philadelphia), Phenom unveiled WorkOps — a new AI platform architecture built around six integrated layers and a governing Orchestration Engine. The launch, combined with its January 14 acquisition of Included AI, signals a deliberate repositioning: from recruiting automation tool to a full HR work-execution platform.

The Problem WorkOps Is Designed to Solve

Phenom cites a striking figure: according to the company, 95% of enterprise AI implementations fail. Whether or not that number holds up to independent scrutiny, the premise resonates with HR leaders who have watched expensive deployments stall in pilot phases, produce generic insights, or quietly fall out of use.

The company's diagnosis is that most AI tools operate in isolation — solving narrow tasks without connecting to the broader context of how work actually gets done. WorkOps is Phenom's answer: a structured, layered architecture designed to integrate intelligence, governance, and execution in a single platform.

The 6-Layer Architecture

WorkOps is built on six named layers, each serving a distinct function:

Engines — the core powering enterprise-scale talent operations
Ontologies — the intelligence layer mapping work, skills, and people connections
XAI (Explainable AI) — a shared capability layer providing trustworthy, flexible intelligence
Experiences — AI embedded directly into talent interactions
Use Cases — workforce-specific AI applications
Agents — AI agents executing talent operations end-to-end

This layered approach reflects a deliberate architectural choice: build shared infrastructure once, then deploy purpose-built capabilities on top. The benefit for HR teams is consistency — the same intelligence layer governs every workflow, rather than each tool operating with its own logic.

The Orchestration Engine: Governance at Speed

The layer that distinguishes WorkOps from a standard multi-agent platform is the Orchestration Engine. Rather than letting AI agents operate independently, the Orchestration Engine governs them: leaders can create guardrails and routing policies, track decisions with full auditability, and exercise real-time human override when needed.

CEO Mahe Bayireddi captured the design philosophy directly: "Speed without context is chaos."

For compliance-conscious enterprises, this matters. AI systems that move quickly but can't explain their decisions — or be corrected in real time — are a legal and reputational liability. The Orchestration Engine is positioned as the governance layer that makes enterprise AI deployment viable, not just fast.

Four New Agents

Phenom launched four new AI agents as part of the WorkOps platform:

Chief of Staff Agent — strategic orchestration across HR workflows
Skills Validation Agent — verifying skill claims and candidate qualifications
Success Coach Agent — supporting employee growth and development
Compliance Agent — reviewing job descriptions and workflows against regulatory requirements

Each agent operates within the Orchestration Engine's governance framework — meaning its actions are tracked, auditable, and subject to human override. This architecture directly addresses the concern that autonomous AI agents introduce compliance risk when operating without oversight.

The Included AI Acquisition

Phenom's January 14, 2026 acquisition of Included AI added a capability that fills a gap in most enterprise HR stacks: agentic people analytics through natural language queries.

Most HR analytics tools still require analysts to build queries or run reports. The Included AI integration brings predictive signals and workforce data into conversational reach — HR leaders can ask questions in plain language and receive actionable insights, without intermediary steps. Combined with WorkOps, this creates a tighter feedback loop: AI agents execute work, the Orchestration Engine logs decisions, and analytics surfaces patterns — all within one platform.

Value Acceleration Model

Phenom's commercial framing for WorkOps emphasizes speed-to-value. The company's Value Acceleration Model positions ROI delivery in weeks rather than months — a direct contrast to the long implementation cycles that accompany most enterprise software purchases.

This claim is self-reported and should be treated as directionally informative rather than independently verified. But for HR leaders evaluating AI platforms under budget pressure, faster time-to-value is a credible differentiator — if it holds in practice.

IAMPHENOM 2026: Applied AI in Practice

WorkOps was unveiled at IAMPHENOM 2026, Phenom's annual practitioner conference. The March 10–12 Philadelphia event featured 100+ sessions, with over 90% led by practitioners.

Danielle Dibner, Phenom's Executive Director of Global Customer Value, framed the conference's purpose clearly: "There's no other conference like IAMPHENOM for HR and IT professionals. Attendees will experience applied AI designed for their specific challenges, hear candid lessons from leaders doing this work right now and leave with actionable approaches for their organization."

That practitioner-led format matters for context. The sessions weren't product pitches — they were case studies from organizations working through the same AI maturity challenges WorkOps is designed to address.

What This Means for HR Leaders

WorkOps is an architectural argument: the reason most enterprise AI fails is not capability gaps, but integration and governance gaps. Phenom is betting that a structured, layered platform with built-in auditability will outperform point solutions in complex HR environments.

For HR leaders evaluating AI vendors in 2026, the WorkOps launch surfaces a useful comparative question: does your current AI stack have a governance layer? If not, Phenom is making the case that it should.