Perplexity AI for Candidate Research: A Startup's Guide to Smarter Talent Sourcing

Every startup founder knows the pressure: build fast, hire smart, and don't make mistakes. But finding top talent often feels like a slow, manual grind. You can't waste time on inefficient research. A single bad hire can cost your lean team valuable resources – up to 30% of an employee's first-year salary. Sifting through countless profiles and fragmented web data is simply unsustainable for agile startups.

Imagine cutting through the noise, gaining deeper insights, and finding top talent with unprecedented speed and accuracy. This is where Perplexity AI for candidate research becomes your secret weapon. This guide shows you how to use Perplexity AI to transform your talent sourcing. Learn to craft precise search queries, uncover hidden gems, and validate candidate fit more effectively. We'll provide practical, actionable steps to integrate this powerful tool into your workflow. Make smarter, faster hiring decisions. Let's dive in and elevate your talent game.

The Startup Talent Sourcing Challenge: Why Traditional Methods Fall Short

You know Perplexity AI can be a powerful tool. But why is it essential for today's startups? The answer lies in the unique and often brutal landscape of startup talent sourcing.

The High Stakes of Startup Hiring

For early-stage companies, every hire is a critical investment. Unlike large companies with big HR teams, startups use lean hiring models. Resources are scarce, and time is a luxury. This creates intense recruitment challenges. You compete for top talent against well-funded tech giants and other agile startups. The pressure to find the right fit, quickly and affordably, is immense.

Consider the impact of a prolonged hiring cycle: Startups spend an average of 42 days to fill a position, with technical roles often taking longer, highlighting the need for more efficient sourcing (Glassdoor, 'Hiring and Recruiting Trends 2024'). This long time-to-hire can stall product development, delay market entry, and burn through precious runway. For a fast-growing company like Rippling, known for targeted recruiting, every day without a key hire means lost momentum. Founders and hiring managers, already wearing many hats, lack the time for inefficient processes. Learn more about The Cost of a Bad Hire for Startups.

Limitations of Traditional Sourcing

Given these high stakes, traditional candidate sourcing problems are no longer acceptable. Relying only on basic resume screening and manual LinkedIn searches is inefficient. It leads to missed opportunities and suboptimal hires. Sifting through hundreds of applications with generic keywords wastes time and yields diminishing returns. This manual process is also prone to bias. Human screeners unconsciously favor certain backgrounds, potentially overlooking diverse and highly capable candidates.

Resumes are poor indicators of crucial attributes like soft skills and cultural fit. While a resume lists technical skills, it struggles to show a candidate's problem-solving approach, collaboration style, or resilience. These qualities are paramount in a dynamic startup. How do you assess if someone truly embodies the 'builder' mentality of a Stripe or the innovative spirit of a Brex from a two-page document? You can't, effectively. This difficulty in assessing soft skills and cultural fit from resumes alone leads to costly mis-hires and impacts team cohesion. Without deeper insights, you make critical hiring decisions based on incomplete data, leaving much to chance. This is where traditional methods fall short, creating a significant gap that modern solutions must address. Read more from LinkedIn Talent Solutions.

What is Perplexity AI and How It Transforms Candidate Research?

Now, let's explore what Perplexity AI is and how it can transform your candidate research. Imagine having a dedicated research analyst at your fingertips, capable of sifting through the entire internet in seconds to give you a concise, sourced report on any candidate. That's Perplexity AI. It's not just another AI search engine; it's an AI-powered conversational answer engine. It synthesizes information from diverse online sources, giving you summarized, sourced answers instead of just links. For startups, this is revolutionary for candidate research.

Beyond a Search Engine: The Power of AI Synthesis

Perplexity AI acts as a virtual research assistant, moving beyond simple keyword matching. When you ask about a candidate, it intelligently gathers data from many public sources: GitHub, LinkedIn, personal blogs, news articles, academic papers, and social media. This deep synthesis provides a more nuanced understanding of a candidate's potential, contributions, and interests than a resume or quick LinkedIn scan.

This level of recruitment intelligence helps you move past surface-level qualifications. You can uncover specific projects, open-source contributions, thought leadership (via blog posts), or news mentions related to their past roles. This comprehensive view is crucial for effective candidate vetting AI. It helps you assess not just what they've done, but how they think and where their true passions lie. As Josh Bersin, a global industry analyst, aptly puts it, “AI isn't just about automation; it's about augmentation. It empowers recruiters to move beyond transactional tasks and focus on strategic talent advisory, leveraging data to make more informed decisions.” Bersin by Deloitte, 'HR Technology Market 2024: The Rise of AI in HR'.

A Virtual Research Assistant for Lean Teams

For startups, where every hire is critical and resources are thin, Perplexity AI is a game-changer. You don't have large recruiting teams or big research budgets. This is where AI recruiting tools like Perplexity AI shine. They democratize deep research capabilities, once only for large enterprises.

Companies like Stripe or Rippling are known for rigorous, data-driven hiring. They deep-dive into candidates' open-source contributions, technical blogs, and community engagement. While they build internal tools, Perplexity AI offers similar depth. Lean startup teams can achieve comparable research quality without the overhead. It significantly reduces the average 42 days startups spend to fill a position (Glassdoor, 'Hiring and Recruiting Trends 2024') by streamlining the initial research phase. This efficiency creates a competitive advantage, especially in niche technical roles where competition for top talent is fierce. Companies that leverage AI in their hiring processes report a 25% increase in hiring efficiency and a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025').

Key Actions for Founders:

• Augment Sourcing: Use Perplexity AI to enrich profiles found on LinkedIn or GitHub, gaining deeper context on projects and contributions.
• Prepare for Interviews: Generate targeted questions based on AI-synthesized insights into a candidate's specific experiences and interests.
• Identify Hidden Gems: Uncover candidates from non-traditional backgrounds whose potential might be missed by traditional resume screening.

By integrating Perplexity AI into your hiring workflow, you transform your candidate research strategies from a time-consuming chore into a strategic advantage. This ensures you make more informed, data-driven decisions for your startup's most critical asset: its people. Explore The Future of AI in Talent Acquisition.

Why Startups Need Perplexity AI for Smarter Talent Sourcing

Building on how Perplexity AI transforms research, let's look at why it's so crucial for startups. As a founder, you know every hire at a startup is mission-critical. Unlike large enterprises with vast recruiting teams, startups use a lean sourcing strategy. Efficiency and precision are paramount. This is where AI, especially tools like Perplexity AI, becomes an indispensable partner – not just an optional add-on. The global HR technology market, including AI recruiting tools, is projected to reach $49.7 billion by 2026 (CB Insights, 'HR Tech Market Report 2024'), signaling a clear shift towards AI-driven talent acquisition.

Leveling the Playing Field Against Larger Competitors

Startups often face an uphill battle against well-funded giants for top talent. You don't have endless time or resources. Perplexity AI acts as your virtual research assistant, helping your small team punch above its weight. It helps you quickly identify niche talent pools that larger companies might miss. It synthesizes vast public data from GitHub, LinkedIn, personal blogs, and news articles. For example, fast-growing companies like Rippling, known for targeted recruiting, could use Perplexity AI to rapidly generate nuanced insights into a candidate's background and fit. This avoids needing a dedicated research department. This is crucial when startups spend an average of 42 days to fill a position (Glassdoor, 'Hiring and Recruiting Trends 2024'), a timeline that can cripple growth.

Boosting Efficiency and Candidate Quality

The data is clear: companies that leverage AI in their hiring processes report a 25% increase in hiring efficiency and a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025'). This isn't just about speed; it's about making better hires. AI recruiting benefits go beyond automation. They empower recruiters to focus on strategic talent advisory, moving past manual resume screening. As Josh Bersin, a global industry analyst, puts it, “AI isn't just about automation; it's about augmentation. It empowers recruiters to move beyond transactional tasks and focus on strategic talent advisory, leveraging data to make more informed decisions.” Bersin by Deloitte, 'HR Technology Market 2024: The Rise of AI in HR'. For a fintech unicorn like Brex, focused on top-tier engineering talent, Perplexity AI could augment research. It rapidly summarizes complex technical projects and market trends relevant to a candidate's experience, saving recruiter time and enhancing hiring efficiency.

Uncovering the 'Why' Behind a Candidate's Journey

Traditional resumes often tell only part of the story. Perplexity AI helps you go deeper. It uncovers candidates from non-traditional backgrounds and helps you understand their potential beyond bullet points. By synthesizing information about a candidate's open-source contributions, technical blogs, and community engagement, you can mitigate bias in traditional screening methods. Stripe, for example, is known for rigorous, data-driven hiring. They deep-dive into candidates' public contributions. Perplexity AI could significantly streamline this deep research, allowing even smaller startups to achieve similar depth. This comprehensive view helps you assess not just skills, but also cultural fit and the 'why' behind their career choices. This leads to higher candidate quality and more successful long-term hires. Learn more about Mitigating Bias in AI Recruiting.

How to Leverage Perplexity AI for Deep Candidate Vetting

Now, let's dive into how to use Perplexity AI for deep candidate vetting. For startups, every hire is a make-or-break decision. You need to move beyond resumes to truly understand a candidate's potential, contributions, and alignment with your vision. This is where Perplexity AI candidate research becomes an invaluable asset. It acts as your virtual research assistant for deep candidate research and elevates your candidate vetting AI processes. It empowers lean teams to achieve insights typically reserved for larger companies with dedicated research departments.

Companies that leverage AI in their hiring processes report a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025'). This isn't just about speed; it's about making smarter, more informed hiring decisions.

Crafting Effective Prompts for Rich Insights

The power of Perplexity AI lies in asking the right questions. Instead of generic searches, craft prompts that target specific, actionable insights about candidates. Think like an investigative journalist, not just a keyword searcher.

• Focus on Contributions, Not Just Roles: Ask, "Summarize [Candidate Name]'s key contributions to [Project Name] at [Company Name], specifically noting any open-source work or public presentations." For a candidate from a company like Stripe, known for its rigorous hiring, you might ask, "What are [Candidate Name]'s publicly available technical writings or conference talks that demonstrate their expertise in [specific technology]?"
• Uncover Domain Expertise and Cultural Alignment: To identify candidates with specific domain expertise and cultural alignment, as practiced by companies like Brex, prompt Perplexity AI with questions like, "Analyze [Candidate Name]'s public statements or blog posts for insights into their philosophy on [relevant industry trend] or [company value]." This helps you gauge their thought leadership and how well their values resonate with your startup's culture.
• Example: If you're hiring for a FinTech role, a prompt could be: "What are [Candidate Name]'s public contributions or discussions related to blockchain technology or payment processing innovation?"

Building Comprehensive Candidate Profiles

Perplexity AI excels at synthesizing information from diverse online sources – GitHub, LinkedIn, personal blogs, news articles, academic papers, and more. This builds a truly comprehensive candidate profile. This goes far beyond what a resume can convey.

• Synthesize Diverse Data Points: Use prompts like, "Compile a summary of [Candidate Name]'s professional journey, highlighting key projects, interests outside of work (if publicly available), and any public speaking engagements or community involvement." This helps you understand their full potential, as Kevin Wheeler, Founder of The Future of Talent Institute, notes: “The next frontier in talent sourcing is not just finding candidates, but truly understanding their potential beyond their resume.” Future of Talent Institute.
• Understand the 'Why': Companies like Rippling emphasize understanding the 'why' behind a candidate's career choices. Perplexity AI can help by summarizing news about their previous companies, market shifts they navigated, or even their personal statements on platforms like Medium.
• Actionable Takeaway: Use the synthesized information to formulate targeted interview questions that probe deeper into their motivations, problem-solving approaches, and alignment with your startup's mission.

Market Intelligence and Competitive Analysis

Beyond individual candidate profiles, Perplexity AI is a powerful tool for recruitment intelligence and informing your AI sourcing strategies.

• Identify Niche Talent Pools: For startups competing for top talent, especially in niche technical roles, understanding where talent gathers is crucial. Prompt Perplexity AI with, "What are the emerging companies or open-source communities focused on [specific technology, e.g., Rust in Web3]?" or "Who are the key influencers and contributors in the [specific industry] space?" As Jeanne Meister of Future Workplace suggests, AI-powered research can help lean teams "quickly identifying and understanding niche talent pools that larger companies might overlook." Future Workplace.
• Competitive Landscape Analysis: Understand what your competitors are doing. Ask, "What are the recent hiring trends or key hires at [Competitor Company A] and [Competitor Company B] in the [specific role] domain?" This intelligence can help you refine your value proposition and target your outreach more effectively.
• Actionable Takeaway: Integrate this market intelligence into your overall AI sourcing strategies to proactively identify and engage with top talent before your competitors do.

Integrating Perplexity AI into Your Existing recruitment workflow

After exploring how AI boosts competitive intelligence and proactive sourcing, the next crucial step is to seamlessly integrate these powerful AI recruiting tools into your daily operations. For lean startup teams, efficiency is paramount. Perplexity AI doesn't replace your existing systems; it augments them. It acts as a sophisticated research assistant, enriching your recruitment workflow with real-time, synthesized intelligence.

Enhancing Your ATS/CRM with AI-Powered Insights

Your Applicant Tracking System (ATS) and Candidate Relationship Management (CRM) are the backbone of your hiring process. Tools like Greenhouse and Lever are essential for managing candidates. But they often lack the deep insights needed to truly understand a candidate beyond their resume. This is where Perplexity AI shines.

Imagine a candidate profile in Greenhouse for a Senior Backend Engineer. Instead of just seeing past roles, Perplexity AI quickly synthesizes information from GitHub contributions, technical blogs, conference talks, and news articles about previous projects. This allows you to enhance candidate records with real-time, synthesized intelligence. It provides a holistic view of their technical prowess, problem-solving approach, and even potential cultural fit. For a fast-growing startup like Rippling, which emphasizes understanding the "why" behind a candidate's career choices, this deep dive is invaluable. Companies that leverage AI in their hiring processes report a 25% increase in hiring efficiency and a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025'). This augmentation helps you move beyond basic keyword matching to a more nuanced assessment, improving overall candidate quality.

Actionable Takeaway:

• Enrich Profiles: Before reaching out or scheduling an interview, use Perplexity AI to generate a concise summary of a candidate's public contributions and interests. Paste these insights directly into custom fields within your ATS (e.g., Greenhouse, Lever) to create richer, more informed candidate profiles. This is a key aspect of effective ATS integration.

Streamlining Sourcing and Outreach with Intelligence

Effective sourcing and outreach are critical for startups competing for top talent. Tools like LinkedIn Recruiter and Gem are excellent for identifying candidates and managing communication. But your outreach quality depends on the relevance and personalization of your message. Perplexity AI provides the intelligence layer that transforms generic messages into highly targeted, compelling communication.

By using Perplexity AI to research a candidate's recent projects, publications, or company news, you can craft personalized messages that resonate. For instance, if you're targeting an engineer for a fintech role at Brex, Perplexity AI can quickly surface their contributions to an open-source financial library or their insights on a recent market trend. This allows you to streamline sourcing and outreach with AI-generated insights for personalized communication. You demonstrate genuine interest and understanding of their work. As Jeanne Meister, Executive Vice President at Future Workplace, notes, “AI-powered research tools can be a game-changer, allowing lean teams to punch above their weight by quickly identifying and understanding niche talent pools.” This targeted approach is crucial for startups facing intense competition and limited resources, making your talent acquisition tech stack more powerful.

Actionable Takeaway:

• Personalize Outreach: Before sending an InMail via LinkedIn Recruiter or an email campaign through Gem, use Perplexity AI to find a specific, relevant detail about the candidate's work or interests. Reference this detail in your opening line to immediately capture their attention and demonstrate that you've done your homework. This elevates your CRM for recruiting strategy.
• Identify Niche Talent: Leverage Perplexity AI to research specific technical communities, forums, or academic papers to uncover hidden gems and niche experts that might not be immediately visible on traditional platforms.

Integrating Perplexity AI into your existing recruitment workflow empowers your team to make more informed decisions, save valuable time, and ultimately, secure the best talent for your startup.

Beyond Skills: Assessing Soft Skills and Cultural Fit with AI-Augmented Research

Beyond finding niche talent, a startup's success hinges not just on what a candidate knows, but who they are and how they work. For lean startup teams, every hire is critical. Accurately assessing soft skills and cultural fit is paramount. Yet, these crucial elements are difficult to gauge from a resume alone, often leading to costly mis-hires. This is where AI-augmented research transforms your approach, moving beyond traditional candidate sourcing strategies to provide deeper, actionable insights.

Uncovering Behavioral Cues and Contributions

Imagine a virtual research assistant that can synthesize a candidate's entire public professional footprint. Our candidate vetting AI does exactly that. It delves into public profiles, project contributions (like GitHub repos), technical blogs, and community discussions. This finds tangible evidence of critical soft skills. For instance, it can highlight instances of:

• Collaboration: Identifying contributions to team projects, mentorship activities, or cross-functional initiatives.
• Leadership: Spotting roles in open-source project governance, leading technical discussions, or guiding junior developers.
• Problem-solving: Analyzing how candidates articulate solutions to complex technical challenges in forums or blog posts.
• Communication: Evaluating clarity in documentation, presentation materials, or public explanations of technical concepts.

This deep soft skills assessment goes far beyond keywords. It provides a nuanced understanding of a candidate's working style and potential impact. Companies like Stripe, known for rigorous hiring, often conduct similar deep dives into candidates' open-source contributions and community engagement. AI can streamline this process, allowing even small teams to achieve such depth. Companies that leverage AI in their hiring processes report a 25% increase in hiring efficiency and a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025').

Crafting Insightful Interview Questions

With these AI-generated insights, your interview process becomes significantly more targeted and effective. Instead of generic questions, you can develop structured interview questions based on specific examples from a candidate's past work. If the AI identifies a candidate who frequently contributed to a complex open-source project, you can ask: "Tell me about a specific challenge you faced in Project X and how you collaborated with the team to overcome it." This approach is vital for assessing cultural fit.

For startups like Rippling, which emphasize understanding the 'why' behind a candidate's career choices and their potential fit beyond just skills, AI-powered recruitment intelligence quickly generates these nuanced insights. It synthesizes information from diverse online sources to build a holistic candidate view. This helps you understand their motivations and alignment with your startup's values.

Furthermore, this data-driven approach is a powerful tool for bias mitigation in hiring. By focusing on objective evidence of contributions and behaviors, rather than subjective resume interpretations, AI helps identify diverse talent pools and candidates from non-traditional backgrounds. This broadens your reach and ensures you build a truly inclusive, high-performing team.

By integrating AI-augmented research into your hiring, you move beyond surface-level evaluations. You gain a strategic advantage, making every hire a more informed decision.

• Leverage AI to analyze public data for concrete examples of soft skills.
• Design structured interview questions directly from AI-generated insights.
• Use AI to proactively identify and engage diverse talent, reducing unconscious bias.

Common Pitfalls and Best Practices for AI-Powered Candidate Research

While AI-augmented research offers a strategic advantage, making every hire more informed, it's crucial to use it with care. The power of AI in recruitment, while promising Companies that leverage AI in their hiring processes report a 25% increase in hiring efficiency and a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025'), comes with responsibilities. For startups, where every hire is critical, understanding common pitfalls and adopting best practices is paramount to truly harness AI's potential.

Human Oversight and Critical Evaluation

The most fundamental principle of responsible AI in hiring is that AI serves as an augmentation tool, not a replacement for human judgment and interaction. As Josh Bersin aptly puts it, “AI isn't just about automation; it's about augmentation. It empowers recruiters to move beyond transactional tasks and focus on strategic talent advisory, leveraging data to make more informed decisions.” Always maintain human oversight and critically evaluate AI outputs to avoid over-reliance. For instance, if Perplexity AI generates a profile for an engineer at Stripe, highlighting open-source contributions, a human recruiter must still delve into the code, assess its impact, and conduct interviews to verify fit and depth. AI can quickly surface insights, but your expertise is essential to interpret and act on them effectively. This is a core tenet of candidate research best practices.

Avoiding Bias and Ensuring Fairness

One of the most significant challenges in AI-powered recruitment is the potential for AI bias in hiring. AI models learn from historical data. This can inadvertently perpetuate existing human biases, leading to less diverse candidate pools. To mitigate this, actively cross-reference information and challenge AI outputs. For a fast-growing startup like Rippling, which values understanding a candidate's 'why' beyond just skills, relying solely on AI without human review could overlook unconventional but highly valuable talent. Use AI to identify diverse talent pools and uncover candidates from non-traditional backgrounds. But always review the results with a critical eye. Ensure your prompts encourage broad searches, and actively seek out information that might counteract potential biases, fostering true AI recruiting ethics.

Data Privacy and Ethical Considerations

Adhering to data privacy recruitment and ethical considerations is non-negotiable. When using AI for candidate research, it is imperative to use only publicly available information. Tools like Perplexity AI excel at synthesizing data from public sources: LinkedIn profiles, public GitHub repositories, personal blogs, and news articles. However, recruiters must ensure they are not attempting to access or use any private data. This commitment to transparency and respect for individual privacy is fundamental to AI recruiting ethics. Always be mindful of regulations like GDPR and CCPA, and your company's internal privacy policies. Building trust with candidates starts with ethical data handling.

By embracing these best practices – human oversight, active bias mitigation, and data privacy – startups can leverage AI as a powerful, ethical assistant. It's about empowering your team to make smarter, faster, and fairer hiring decisions, not replacing the invaluable human element. Learn more about AI recruiting ethics.

Conclusion: Empower Your Startup's Hiring with Perplexity AI

After exploring the ethical considerations of AI in hiring, it's clear: when used responsibly, AI is a strategic advantage for startups. For lean startup teams, finding top talent is an immense challenge. You compete with giants, often with limited budgets and time. This is where Perplexity AI candidate research becomes a game-changer. It offers a powerful, cost-effective solution for smarter startup talent sourcing and deeper candidate research, acting as your virtual research assistant. Imagine cutting down the average 42 days it takes for startups to fill a position (Glassdoor, 'Hiring and Recruiting Trends 2024') by quickly synthesizing public data on candidates' projects, contributions, and interests.

Embracing AI recruiting tools can significantly improve hiring efficiency, candidate quality, and your competitive advantage. Companies leveraging AI report a 25% increase in hiring efficiency and a 15% improvement in candidate quality (Gartner, 'Future of HR: AI in Talent Acquisition 2025'). As Josh Bersin aptly puts it, “AI isn't just about automation; it's about augmentation. It empowers recruiters to move beyond transactional tasks and focus on strategic talent advisory...” Bersin by Deloitte, 'HR Technology Market 2024: The Rise of AI in HR'.

The Future of Startup Talent Acquisition is Here

The future of hiring is undeniably augmented by AI. This allows lean teams to make more strategic and informed hiring decisions. The global HR technology market, projected to reach $49.7 billion by 2026 (CB Insights, 'HR Tech Market Report 2024'), underscores this rapid shift. Think about how companies like Stripe or Rippling deep-dive into candidates' open-source contributions and community engagement. Perplexity AI allows even the smallest startup to achieve this nuanced understanding. It quickly generates comprehensive profiles that go beyond a resume. This means you can identify niche talent pools and truly understand a candidate's potential, just as Jeanne Meister suggests, “For startups, every hire is critical. AI-powered research tools can be a game-changer...” Future Workplace, 'AI and the Future of Work' insights. This is precisely why Clera.io exists. We provide an AI-powered recruiting platform designed specifically for startups. It streamlines and optimizes your entire hiring process, from intelligent sourcing to candidate engagement.

Ready to Transform Your Hiring?

Don't let limited resources hold you back from securing the best talent. Here’s how you can empower your startup's hiring today:

• Leverage AI for Deep Insights: Use tools like Perplexity AI to conduct rapid, comprehensive candidate research, uncovering projects, contributions, and cultural fit indicators that traditional methods miss. Explore Advanced Candidate Sourcing Strategies.
• Boost Efficiency: Reduce time-to-hire and free up your team to focus on high-value interactions, not manual data gathering. 83% of recruiters believe AI will significantly change the recruiting landscape in the next 5 years (LinkedIn Talent Solutions, 'Global Talent Trends 2024').
• Make Strategic Decisions: With richer data at your fingertips, you'll make more informed choices, leading to higher quality hires and a stronger competitive edge.
• Embrace Clera.io: Explore how our platform integrates these AI capabilities, offering a tailored solution to help your startup scale effectively and build an exceptional team. Discover Clera.io Features.