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.

Harper by Wisq: Inside the First AI HR Generalist Resolving 40% of HR Tickets Autonomously

2026-06-19

Most AI tools in HR do one thing. A chatbot answers benefits questions. A scheduling bot manages shifts. A screening tool filters resumes. Each solves a narrow problem — and each requires its own integration, its own maintenance, its own learning curve.

Wisq's Harper is built on a different premise: what if an AI could work across the full breadth of HR operations the way a seasoned generalist does?

Launched in February 2025, Harper is what Wisq calls "the world's first AI HR Generalist" — an autonomous agent that handles leave management, time and attendance, return-to-office enforcement, benefits inquiries, performance improvement plans, bias detection in performance reviews, and manager coaching, all from a single platform (Wisq press release, Feb 2025).

The claim is ambitious. The early evidence, while vendor-reported, is worth examining.

The Technical Foundation: HRLM

What separates Harper from a generic chatbot layered with HR prompts is its underlying model. Wisq built HRLM — which the company describes as the first large language model purpose-built for enterprise HR — trained specifically on HR policy, labor law, and regulatory frameworks (FutureTekNow).

On Wisq's proprietary Hurdle benchmark — designed to evaluate AI on HR-specific tasks — HRLM matches the performance of OpenAI's o3 model while running faster and at lower cost, according to the company (FutureTekNow). It is worth noting that Hurdle is Wisq's own benchmark, not an independently validated industry standard. The comparison to o3 is directionally informative but should be understood in that context.

For HR leaders evaluating AI literacy, the Hurdle benchmark results offer a concrete reference point for the model's domain depth — though independent validation would strengthen that case.

What Harper Actually Does

Harper's capabilities span the operational core of HR generalist work:

Policy and compliance automation: Time and attendance tracking, return-to-office policy enforcement, leave of absence management, and benefits question resolution (Wisq press release, Feb 2025)
Employee support: 24/7 responses to employee questions with proactive guidance through complex processes (Wisq blog)
Performance management: AI-driven pre-calibration for feedback analysis, real-time performance monitoring, PIP construction, and bias detection in performance reviews (Wisq blog)
Manager coaching: Always-on coaching with customized development pathways and leadership behavior reinforcement (Wisq blog)

The breadth is what substantiates the "generalist" label. This is not a chatbot that escalates to a human after two turns — according to Wisq, Harper resolves 40% of HR tickets fully autonomously (Fast Company PR, 2026), with 80% or more of routine queries handled without human intervention (Wisq blog).

Real-World Results

Two case studies illustrate the practical impact:

Manufacturing client: According to Wisq, HR team members saved 35 hours per month each through automated policy case handling. That is roughly a full work week returned to strategic priorities every month (Wisq blog).

Fintech client: The company reports a 70%+ improvement in performance feedback outcomes after deploying Harper's performance management capabilities (Wisq blog).

These are vendor-reported metrics without independent verification, but they point to measurable operational impact in production environments.

The Team and the Backing

Wisq was founded in 2022 by the team behind Glint — the employee engagement platform acquired by LinkedIn. That pedigree matters: this team has built enterprise HR software at scale before (Wisq press release, Feb 2025).

The company has raised $55 million in total funding from Norwest Venture Partners, Shasta Ventures, and True Ventures, including a recent $15 million round earmarked for expanding engineering and go-to-market teams (FutureTekNow; Fast Company PR, 2026).

The market has noticed. Fast Company ranked Wisq #2 on its Most Innovative Companies in Human Resources list for 2026, and Harper was named a Top HR Product of the Year by HR Executive in 2025 (Fast Company PR, 2026).

What This Signals for HR

Harper represents a specific bet about where HR technology is heading: from point solutions to autonomous generalists. Rather than assembling a patchwork of single-purpose bots, the agentic model puts a single AI teammate across multiple HR workflows — one that reasons through policy, takes action across systems, and learns from each interaction.

For HR leaders evaluating this space, the questions are practical. Can an AI generalist reduce the operational load enough to justify consolidating tools? Does a purpose-built HR model outperform general-purpose LLMs on the edge cases — the FMLA-ADA intersections, the multi-state leave calculations — that actually consume HR time?

Wisq's early numbers suggest the answer is yes, at least directionally. As agentic HR platforms mature through 2026, expect the "generalist vs. specialist" debate to become central to every HR tech stack decision.

Does Harper replace human HR professionals?

No. According to Wisq, Harper is designed to augment HR teams by autonomously handling routine operational tasks — policy questions, time-and-attendance issues, leave management — so human HR professionals can focus on strategic work. The company reports that 40% of HR tickets are resolved autonomously, but complex decisions and employee relations remain human-led.

How does HRLM differ from using a general-purpose AI model like GPT-4 or Claude for HR tasks?

HRLM is purpose-built for HR, trained specifically on HR policy, labor law, and regulatory frameworks rather than fine-tuned from a general-purpose model. Wisq reports it matches OpenAI o3 on HR-specific tasks (per their proprietary Hurdle benchmark) while running faster and more affordably. Independent benchmarking would strengthen that claim, but the domain-specific training approach represents a meaningful architectural difference.

Is Wisq's pricing publicly available?

As of March 2026, Wisq has not published public pricing for Harper. HR teams interested in evaluating the platform should contact Wisq directly for enterprise pricing details.