How Does LinkedIn Hiring Assistant Work? (w/Examples) + FAQs

LinkedIn Hiring Assistant works as an AI agent that lives inside LinkedIn Recruiter, reading a job description, sourcing candidates from LinkedIn’s billion‑member network, screening and ranking them, drafting outreach, answering applicant questions, and even helping schedule interviews. It is a plan‑and‑execute agent, meaning each recruiter gets their own stateful agent instance that remembers context, learns from feedback, and runs long workflows in the background while the recruiter focuses on people work.

The legal hook matters as much as the tech. Hiring Assistant qualifies as an Automated Employment Decision Tool (AEDT) under NYC Local Law 144, and it sits inside the federal anti‑discrimination guardrails of Title VII of the Civil Rights Act and the Americans with Disabilities Act. Skip the bias audit, the candidate notice, or the human review, and you can face fines, EEOC charges, and class action exposure.

According to LinkedIn’s own 2025 Future of Recruiting report, recruiters spend up to 30 hours a week on repetitive sourcing and screening, which is the time Hiring Assistant is built to claw back.

Here is what you will learn in this guide:

• 🤖 How LinkedIn Hiring Assistant’s agent architecture sources, screens, and messages candidates step by step
• 💵 What it costs across Recruiter Lite, Professional, and Corporate in 2026
• ⚖️ Which federal and state laws (EEOC, ADA, NYC 144, Illinois AIVIA, Colorado AI Act) apply to your use of it
• 🧪 Three real hiring scenarios with named examples showing wins, traps, and consequences
• 🚫 The most common mistakes recruiters make and how to avoid each one before HR or legal gets involved

What LinkedIn Hiring Assistant Actually Is

LinkedIn Hiring Assistant is an agentic AI add‑on to LinkedIn Recruiter, first announced in late 2024 and rolled out broadly through 2025 and into the 2026 Hiring Release Wave 1. It is not a chatbot bolted on the side of Recruiter. It is a planning agent that takes a recruiter goal, like “fill this senior backend engineer role in Boston,” and breaks it into sub‑tasks, executes them, and reports back.

LinkedIn engineers describe Hiring Assistant as a stateful real‑time agent with a supervisor that plans, sub‑agents that execute, and a memory layer that holds preferences across sessions. Each recruiter has their own instance with its own mailbox and identity. That separation matters for privacy, auditability, and personalization, because one recruiter’s feedback does not silently steer another recruiter’s pipeline.

The product is sold as part of LinkedIn Recruiter, and LinkedIn confirms Hiring Assistant is an add‑on, meaning you pay for the underlying Recruiter seat plus the Hiring Assistant capability on top. It is not bundled into Recruiter Lite at the same depth, which is why pricing tiers matter.

The feature set covers six core jobs: intake, sourcing, screening, ranking, outreach, and candidate Q&A. A seventh, scheduling and follow‑ups, was added in the 2025 product update that introduced automated candidate follow‑ups and basic role question handling.

The plain‑English version is simple. Hiring Assistant takes the busywork off your plate so you can spend more time talking to humans. The consequence of using it badly is that it talks to humans for you in ways you cannot defend later, which is where compliance enters the picture.

Why LinkedIn Built It

LinkedIn built Hiring Assistant because recruiters were drowning. Internal data cited in LinkedIn’s Future of Recruiting shows recruiters spend a majority of their week on tasks that do not require human judgment, like keyword searching, resume reading, and follow‑up emails. The plain‑English explanation is that AI is good at pattern matching and bad at empathy, so LinkedIn handed pattern matching to the agent.

The consequence of not automating these tasks is slow time‑to‑hire and recruiter burnout. The U.S. Bureau of Labor Statistics tracks recruiter turnover, and SHRM has reported recruiter turnover above 40% in some sectors during peak hiring cycles. A real‑world example is a staffing agency named Bright Path Talent that lost two senior recruiters in a quarter because they were stuck doing keyword Boolean searches at midnight, which is exactly the work Hiring Assistant is designed to remove.

A common misconception is that Hiring Assistant replaces recruiters. It does not. LinkedIn explicitly markets it as an assistant for recruiters, not a replacement, and federal anti‑discrimination law effectively forces a human in the loop anyway because the employer remains liable for any decision the tool drives.

How It Differs From Older LinkedIn AI

Older LinkedIn AI features helped one task at a time. Recommended Matches, AI‑assisted messages, and AI‑assisted search each lived in their own corner of Recruiter. Hiring Assistant ties them together with a planner, so the same agent that found the candidate also writes the InMail and tracks the reply.

The consequence of this shift is that the agent can chain steps without the recruiter clicking through each screen. The example here is a recruiter named Lena at a fintech who used to open six tabs to source, screen, and message; with Hiring Assistant she gives one prompt and reviews a shortlist with explanations.

A common misconception is that Hiring Assistant is “just GPT inside LinkedIn.” It is not a single LLM call. It is an orchestrated multi‑agent system with retrieval, memory, tool use, and feedback loops, which is why its outputs are tied to LinkedIn’s structured data and not free‑floating hallucinations.

How LinkedIn Hiring Assistant Works Step by Step

Hiring Assistant follows a five‑stage loop that mirrors how a human recruiter works, only faster and at scale. The stages are role intake, qualification review, sourcing, evaluation, and outreach, with scheduling layered in. Brandon Hall Group’s analysis walks through the same flow, and LinkedIn’s own engineering blog confirms the supervisor‑and‑sub‑agent plumbing underneath.

The plain‑English version is that you give it a job, it asks clarifying questions, it goes hunting, it ranks who it finds, it writes them, and it tells you what happened. The consequence of skipping any stage is a weaker shortlist or, worse, a biased one you cannot defend in an audit.

Stage 1: Role Intake

You start by pasting a job URL, a job description, or a LinkedIn Jobs post. Hiring Assistant extracts the title, location, seniority, must‑have skills, and nice‑to‑have skills. It also pulls company context from your LinkedIn company page so it understands your industry and stack.

The consequence of a thin intake is a shallow shortlist, because the agent infers what to look for from what you give it. A real example is a recruiter named Marco at a healthcare startup who pasted only “RN, Boston” and got generic results, then re‑ran the agent with the full job description and saw the shortlist quality jump.

A common misconception is that more detail always helps. It does not. Stuffing the job description with unrelated buzzwords confuses the agent and dilutes the match score, so write tight, skill‑first descriptions.

Stage 2: Qualification Review

The agent proposes required and preferred qualifications based on the job and your past hiring patterns. You can accept, edit, or remove each one. This is the moment to remove proxies for protected traits, which is what the EEOC’s technical assistance on AI warns about.

The consequence of leaving in a sloppy proxy, like “graduated within the last 3 years,” is age discrimination exposure under the Age Discrimination in Employment Act. A real example is a recruiter named Priya who removed a “recent graduate” filter after legal flagged it, which kept her shortlist compliant with the ADEA.

A common misconception is that the AI sanitizes your criteria for you. It does not. It surfaces what worked historically, and historical patterns can encode bias, which is why Mobley v. Workday is now a closely watched federal class action.

Stage 3: Automated Sourcing

The agent searches LinkedIn’s network of more than 1 billion members, looking at profiles, skills, employment history, projects, and signals like “open to work.” It also flags people from companies with recent layoffs and from fast‑growing employers, per LinkedIn’s engineering blog.

The consequence of trusting sourcing blindly is that you may inherit historical hiring bias, because past patterns shape who the agent surfaces first. A real example is a recruiter named Devon who noticed only candidates from three universities in his shortlist, expanded the school list manually, and saw a more diverse pool.

A common misconception is that LinkedIn’s algorithm is neutral. No algorithm trained on past hiring data is fully neutral, and the EEOC has stated that employers remain responsible for disparate impact even when a vendor’s tool produces it.

Stage 4: Candidate Evaluation and Ranking

Hiring Assistant scores each candidate against the qualifications, and it gives a written rationale. That rationale is gold. It is what you can show a hiring manager, and it is what you can review for bias before sending an outreach.

The consequence of ignoring the rationale is that you treat the score like a black box, which is exactly what the Colorado AI Act and Illinois AI Video Interview Act try to prevent. A real example is a recruiter at a Denver software firm who reviewed rationales weekly and caught a pattern where the agent over‑weighted a single keyword, then corrected the weighting.

A common misconception is that the score is the decision. It is a recommendation, and federal guidance is consistent that humans must make the final call to limit liability under Title VII.

Stage 5: Personalized Outreach and Scheduling

The agent drafts InMails tailored to each candidate, referencing their background and your role. It can also handle automated candidate follow‑ups, answer basic role questions, and assist with interview scheduling.

The consequence of letting it auto‑send without review is a tone‑deaf message landing in a senior leader’s inbox, which can burn the relationship for years. A real example is a recruiter named Ana whose first auto‑drafted note used a candidate’s outdated title; she now reviews each draft before send.

A common misconception is that AI outreach is “spam.” Done right, with personalization grounded in real profile data, response rates rise, and LinkedIn has reported double‑digit lifts on internal pilots referenced in the 2026 Hiring Release notes.

LinkedIn Hiring Assistant Pricing in 2026

LinkedIn Hiring Assistant is not free, and it is not sold as a standalone. It is an add‑on to a Recruiter seat, and the depth of its features changes with the tier. Independent reviews like Postipy’s 2026 pricing guide and Augtal’s breakdown line up with public list prices.

The plain‑English version is that solo recruiters get a stripped‑down version, mid‑market staffing agencies get the full agent, and enterprises get the full agent plus deeper automation and ATS sync. The consequence of buying the wrong tier is paying for seats you cannot fully use, or worse, paying for Lite and discovering it does not include the automation you need.

2026 Pricing by Tier

The consequence of upgrading mid‑contract is usually a co‑terminus seat increase, and LinkedIn does not publish standardized discounts, so you negotiate. A real example is a 50‑person staffing firm named Crestline Search that bundled 12 Corporate seats with a 14‑month term and won roughly 18% off list, which is consistent with patterns reported in Augtal’s 2026 cost guide.

A common misconception is that Hiring Assistant is “just turned on” once you pay. Most rollouts require an admin to assign the add‑on per seat in Recruiter admin settings, and Hiring Assistant access is gated by region, role, and contract.

What You Actually Get at Each Tier

Lite gives you AI‑recommended matches and basic message drafting, but no agentic workflows, per Postipy’s 2026 review. Professional unlocks the full agent, including automated sourcing, ranked shortlists, candidate Q&A, and scheduling assistance. Corporate adds enterprise ATS sync, advanced reporting, and the broadest InMail allotments.

The consequence of buying Lite for an enterprise team is that you cannot run the multi‑step workflows that justify the spend. A real example is a Series B startup named Northwind Robotics that bought five Lite seats, hit a wall on automation, and re‑papered to Professional within 90 days.

A common misconception is that InMail caps do not matter when AI writes them. They matter more, because Hiring Assistant can burn through credits fast if you let it auto‑send, which is why LinkedIn caps InMail at 30, 100, and 150 per month across the three tiers.

U.S. Legal and Compliance Landscape

Hiring Assistant runs inside one of the most regulated corners of HR tech. Federal law sets the floor, and a growing patchwork of state and city laws stack on top. Treat this section as the minimum you need to brief legal on before you turn the agent loose.

The plain‑English version is that the federal government cares about discrimination outcomes, while states and cities care about transparency, audits, and notices. The consequence of ignoring either layer is regulator action, civil suits, or both, with NYC and Illinois already enforcing.

Federal Floor: EEOC, Title VII, and the ADA

Title VII of the Civil Rights Act bans hiring decisions that produce disparate impact on protected classes. The EEOC’s 2023 guidance says employers remain liable for AI tool outcomes even when a vendor like LinkedIn built the tool. The ADA technical assistance adds that AI tools must offer reasonable accommodations and cannot screen out disabled candidates.

The consequence of a disparate impact finding is back pay, injunctive relief, and EEOC oversight. A real example is iTutorGroup, which the EEOC settled with for $365,000 over an AI screening tool that filtered out older applicants.

A common misconception is that LinkedIn carries the legal risk. It does not. The employer is the covered entity under Title VII, and indemnification clauses in vendor contracts rarely reach EEOC enforcement.

City and State: NYC Local Law 144

NYC Local Law 144 requires an independent bias audit within the prior 12 months before any AEDT can be used to substantially assist or replace a hiring decision in New York City. Employers must publish a summary of audit results and notify candidates at least 10 business days in advance.

The consequence of using Hiring Assistant in NYC without a current bias audit is fines starting at $500 per violation and rising to $1,500 per day per the NYC DCWP rules. A real example is a Manhattan‑based agency named Hudson Talent Group that paused Hiring Assistant in NYC roles for 30 days while it secured an independent audit from a third‑party assessor.

A common misconception is that LinkedIn’s internal fairness testing satisfies LL144. It does not. The law requires an independent auditor, not the vendor, as confirmed by FairNow’s compliance guide and the New York State Comptroller’s review.

Illinois AI Video Interview Act and HB 3773

The Illinois Artificial Intelligence Video Interview Act requires employer notice, candidate consent, and limited data retention when AI evaluates video interviews. Illinois also amended its Human Rights Act through HB 3773 to cover AI in employment decisions, effective January 1, 2026.

The consequence of skipping notice or consent is a private right of action under the Illinois Human Rights Act. A real example is a Chicago‑based retailer named Loop Apparel Co. that updated its careers page with explicit AI notice language to align with the 2026 amendments.

A common misconception is that the Illinois law only covers video. The 2026 amendments reach broader AI‑assisted decisions, which means Hiring Assistant’s ranking and screening features fall in scope, per analysis from labor and employment counsel covered by SHRM.

Colorado AI Act and the State Wave

The Colorado AI Act, SB24‑205, takes effect February 1, 2026, and regulates high‑risk AI systems, which include hiring tools. It requires risk management programs, impact assessments, and consumer notices.

The consequence of nonconformance is enforcement by the Colorado Attorney General. A real example is a Denver employer named Rocky Mountain Health that built an AI governance committee in 2025 to inventory tools like Hiring Assistant before the February 2026 trigger date.

A common misconception is that Colorado is the only state moving. California’s CCPA automated decisionmaking regulations and several other states are layering rules quickly, which is why a national employer should default to the strictest standard.

The Mobley v. Workday Signal

Mobley v. Workday is a federal class action arguing that an AI hiring vendor can be liable as an agent of the employer under Title VII and the ADEA. The Northern District of California allowed the case to proceed and granted preliminary collective action treatment in 2024 and 2025.

The consequence is that vendor risk and employer risk now overlap, which means your Hiring Assistant procurement contract should include audit cooperation, indemnification, and data access clauses. A real example is a 2,000‑person employer named Beacon Logistics that re‑opened its LinkedIn contract to add an AI fairness rider before the 2026 renewal.

A common misconception is that Mobley only matters for Workday customers. The legal theory reaches any AI hiring vendor, which is why HR and procurement teams are reviewing all hiring AI contracts.

Three Real Hiring Scenarios

The fastest way to see how Hiring Assistant works is to walk three real hiring patterns. Each table below is a 2‑column scenario showing the recruiter move and the resulting outcome.

Scenario 1: SaaS Sales Hiring Sprint

A SaaS company needs 20 enterprise account executives across four U.S. regions in 90 days.

Scenario 2: Hospital Nursing Backfill

A hospital system based partly in NYC needs 60 RNs over six months.

Scenario 3: Startup Senior Hire

A founder hires one staff engineer using a single Recruiter Professional seat.

Three Named Examples From Real Recruiters

The named scenarios below show how individual recruiters use Hiring Assistant, what they gained, and what they had to watch out for.

Example 1: Lena, Fintech Recruiter in Boston

Lena runs talent for a 300‑person fintech and hires 30 engineers a year. She gives Hiring Assistant the JD URL and a short note about team culture. The agent surfaces a 40‑person shortlist with rationales, drafts personalized InMails, and tracks replies inside Recruiter.

The consequence is that Lena’s time‑to‑shortlist drops from five days to under one. She reviews every rationale to keep human judgment in the loop, which is what the EEOC’s AI guidance recommends.

A common misconception people hold about Lena’s setup is that AI replaced her. It did not. Her hiring manager partnership work and offer negotiation work expanded, because she has time for them now.

Example 2: Marco, Healthcare Talent Lead in NYC

Marco hires nurses, techs, and admins for a hospital system with NYC sites. He pauses Hiring Assistant on NYC roles until his independent LL144 bias audit is finalized, then re‑enables it with a public audit summary and a careers‑page notice.

The consequence is that Marco’s program is defensible in a regulator request, which matters because NYC DCWP has authority to fine per violation. He also documents every step he takes, which builds an evidentiary record.

A common misconception is that LinkedIn’s product certification covers Marco’s audit. It does not, and his counsel confirmed an independent third‑party audit is required.

Example 3: Priya, Staffing Agency Owner in Chicago

Priya owns a 12‑person agency placing accounting talent across the Midwest. She pays for two Recruiter Professional seats and uses Hiring Assistant to source 200 candidates a week. She removed an age‑proxy filter and added an Illinois AIVIA notice to her candidate emails.

The consequence is that Priya scaled placements 35% year over year without adding headcount. Her Illinois notice template aligns with HB 3773, which protects her under the 2026 amendments.

A common misconception is that small agencies are too small to enforce against. They are not, and Illinois plaintiffs’ counsel actively pursue smaller employers under the Human Rights Act.

Mistakes to Avoid

Recruiters trip on the same patterns again and again with Hiring Assistant. Avoid these to keep your hiring fast and defensible.

• Skipping the bias audit in NYC. Using Hiring Assistant in NYC without a current independent audit triggers LL144 fines.
• Letting the agent auto‑send InMails. Tone errors and outdated titles burn relationships, and you lose your human in the loop.
• Leaving age proxies in qualifications. Filters like “recent grad” expose you to ADEA claims.
• Treating the score as the decision. EEOC expects a human to make the final call.
• Ignoring ADA accommodation requests. AI cannot screen out disabled candidates without violating the ADA.
• Buying Recruiter Lite for enterprise needs. Lite limits the agentic features you actually need, per Postipy’s review.
• Forgetting candidate notices. NYC, Illinois, and Colorado all require notice before AI is used in hiring decisions.
• Failing to document review steps. No paper trail means no defense in an EEOC charge.
• Trusting historical patterns. Past hiring data can encode bias, and Mobley v. Workday shows the legal theory is live.
• Sourcing only from “top schools.” Narrow filters tank diversity and create disparate impact risk.

Do’s and Don’ts

Do’s

• Do review every match rationale before InMail send, because it preserves your Title VII defense.
• Do post an AEDT notice on your careers page in NYC, because LL144 requires it.
• Do train recruiters to spot proxies, because clean criteria reduce ADEA and Title VII risk.
• Do keep a human approval step on every offer, because vendors do not absorb your liability.
• Do save outputs and rationales, because regulators and plaintiffs both ask for evidentiary records.

Don’ts

• Don’t rely on LinkedIn’s internal fairness as your bias audit, because LL144 needs an independent auditor.
• Don’t share one agent instance across recruiters, because each instance is built to be recruiter‑specific.
• Don’t auto‑send InMails to senior candidates, because a tone miss is hard to recover from.
• Don’t ignore Colorado, Illinois, or California rules just because you are HQ’d elsewhere, because employees are protected where they work.
• Don’t assume the vendor indemnifies you for EEOC enforcement, because the employer is the covered entity.

Pros and Cons

Pros

• Speed: Time‑to‑shortlist drops sharply, because the agent runs sourcing in parallel per LinkedIn engineering.
• Scale: One recruiter can handle multiple roles, because the agent runs background workflows.
• Quality rationale: Each match comes with a written explanation, which supports manager conversations.
• Network reach: Access to 1B+ members means a deeper pool than most ATS sources.
• Personalization: Outreach references real profile data, which lifts response rates.

Cons

• Cost: Recruiter Professional/Corporate run $8,999–$10,800+ per seat per year.
• Compliance overhead: NYC, Illinois, and Colorado layer real obligations onto every deployment.
• Bias inheritance: Historical patterns can carry forward, which is the heart of Mobley v. Workday.
• Vendor lock‑in: Workflows and data live in LinkedIn, so switching ATS is harder.
• InMail caps: Even Corporate caps InMail at 150/month, which limits high‑volume outreach.

Process and Forms: What a Compliant Rollout Looks Like

A compliant rollout has six steps and a paper trail at every step. The plain‑English version is write it down before you turn it on.

Step 1: Inventory. List every place Hiring Assistant will operate, by state and city. The consequence of skipping inventory is missing a jurisdiction trigger like Colorado’s SB24‑205.

Step 2: Bias audit. Engage an independent auditor before NYC use, per LL144. The consequence of skipping it is fines and an unenforceable hiring decision.

Step 3: Notices. Post AEDT notice on the careers page and add notice language to job postings. The consequence of skipping notice is a private right of action in Illinois under HB 3773.

Step 4: Configuration. Turn off auto‑send, require human approval on every InMail, and log rationales. The consequence of skipping configuration is a black‑box program no one can defend.

Step 5: Training. Train recruiters on proxies, ADA accommodations, and review steps. The consequence of skipping training is a recruiter who unknowingly introduces disparate impact.

Step 6: Monitoring. Pull adverse‑impact reports quarterly, and re‑run the audit annually under LL144. The consequence of skipping monitoring is enforcement risk and the kind of evidentiary gap Mobley v. Workday exploits.

Comparing Hiring Assistant to Rival AI Recruiting Agents

Hiring Assistant is the most network‑rich agent because of LinkedIn’s data moat. Rivals lean on different strengths.

The consequence of picking only on price is a tool that does not match your hiring profile. A real example is Northwind Robotics, which evaluated all five and chose Hiring Assistant plus a SeekOut overlay for diversity sourcing.

A common misconception is that Hiring Assistant is “the only AI agent for hiring.” It is one of several, and the right answer often involves more than one tool, layered carefully.

Key Entities to Know

The cast of characters around Hiring Assistant is small but consequential.

• LinkedIn Talent Solutions is the LinkedIn business unit that builds Recruiter and Hiring Assistant.
• EEOC enforces Title VII, the ADA, and the ADEA at the federal level.
• NYC DCWP enforces Local Law 144 and AEDT bias audits.
• Illinois Department of Human Rights enforces the Human Rights Act and HB 3773 amendments.
• Colorado Attorney General enforces SB24‑205 against high‑risk AI systems.
• Independent auditors like those listed under LL144 rules sign off on bias audits.
• Federal courts like the Northern District of California are shaping vendor liability through Mobley v. Workday.

Recap of Relevant Rulings

A handful of decisions and settlements drive how Hiring Assistant should be deployed.

The EEOC v. iTutorGroup settlement confirmed that AI screening producing age discrimination violates the ADEA, with a $365,000 settlement. The plain‑English takeaway is that AI cannot be used to filter candidates by age.

Mobley v. Workday extended potential liability to AI vendors as employer agents under federal antidiscrimination law. The consequence is that procurement contracts now need fairness riders.

NYC DCWP enforcement of Local Law 144 began on July 5, 2023, and continues through 2026. The takeaway is that NYC employers cannot rely on vendor self‑certification.

The Colorado AI Act, SB24‑205, and the Illinois HB 3773 amendments are not court rulings, but their compliance triggers in 2026 are reshaping how AI hiring tools are deployed nationally.

FAQs

Is LinkedIn Hiring Assistant free?

No. It is an add‑on to a paid LinkedIn Recruiter seat, with full features starting at the Recruiter Professional tier in 2026.

Does LinkedIn Hiring Assistant replace recruiters?

No. LinkedIn markets it as an assistant, and federal anti‑discrimination law expects a human to make the final hiring decision.

Is LinkedIn Hiring Assistant subject to NYC Local Law 144?

Yes. When used to substantially assist hiring decisions in NYC, it qualifies as an AEDT and requires an independent bias audit and candidate notice.

Can I use Hiring Assistant in Recruiter Lite?

Yes, but only for basic AI recommendations, not the full agentic workflow available in Professional and Corporate.

Does Hiring Assistant work outside the United States?

Yes, LinkedIn has rolled it out across multiple regions, but data‑protection rules like GDPR add obligations beyond U.S. compliance.

Does Hiring Assistant comply with the ADA?

Yes, but only when the employer configures it to allow accommodations, and the employer remains responsible for ADA compliance.

Is the bias audit done by LinkedIn enough to meet LL144?

No. LL144 requires an independent auditor, not the vendor itself, per the NYC DCWP rule.

Can Hiring Assistant send messages without recruiter approval?

Yes, technically, but doing so increases legal and brand risk, and best practice is to require human review on each message.

Does Hiring Assistant integrate with my ATS?

Yes, especially at the Recruiter Corporate tier, which supports broad enterprise ATS sync.

Will the Colorado AI Act apply to Hiring Assistant?

Yes. It is a high‑risk AI system under SB24‑205, and Colorado employers must run impact assessments starting February 1, 2026.

Does Hiring Assistant store candidate data?

Yes, LinkedIn stores candidate interactions to support recruiter workflows and audit needs, subject to its data‑processing terms.

Can a small agency afford Hiring Assistant?

Yes, smaller firms typically buy one or two Recruiter Professional seats to access the full agent without enterprise commitments.