What Does Perplexity AI Do?

Search Overload: Why Links Lists Waste Your Time

You type a question, get ten blue links, and spend the next hour doing the actual research yourself. That is the quiet failure of traditional search: it hands you a starting point, not an answer.

The problem compounds fast. A single business question — "how are competitors pricing this?" — might require opening six tabs, skimming four articles, and mentally stitching the findings together. The search engine's job ends at the link list; the synthesis work is entirely yours. For managers and professionals who research daily, that synthesis tax quietly eats hours every week.

Perplexity AI was built to eliminate that middle step. The company describes itself as an AI answer engine that researches the open web in real time and returns concise, cited answers — with inline citations on every response so you can verify the claims yourself. Instead of links, you get a synthesized answer grounded in live web sources.

Independent reviewers back up the time savings. A G2 reviewer who used Perplexity for roughly two years reports replacing Google for 95% of daily queries and cutting an hour of research down to twenty minutes. The same review captures the difference in one line: it works "more like a research assistant than a traditional search engine."

What that looks like in practice:

• A cited answer instead of a link list — sources appear inline, making responses checkable rather than take-it-on-faith.
• Multi-model routing — Perplexity sends each query across multiple frontier models, including OpenAI, Gemini, Nvidia, and Claude, so the question is handled by the model best suited for it.
• Research-first workflows — G2 identifies deep research, product research, file analysis, and market research as the strongest fits.

There is an honest caveat worth stating early. One PCMag comparison test found Perplexity's Deep Research the fastest at roughly three minutes, but the shallowest in depth compared with ChatGPT and Gemini. Concise answers trade off against exhaustive analysis — a useful framing for deciding when to reach for it.

The bigger picture is that search is becoming one skill among many an AI agent can perform. Perplexity's own API docs describe a "Perplexity Search skill" that can be installed into coding agents — and if you are equipping agents with skills like that, SkillzBench is building a free directory where such skills can be discovered, security-scanned, and benchmarked before you trust them in a workflow.

For anyone whose work depends on fast, sourced answers, the answer-engine model solves a real, daily frustration — one cited response at a time.

The Four Pillars: From Answer Engine to Agentic Computer

Perplexity started life as a search replacement, but it has quietly grown into something much bigger: a four-part platform that researches, acts, browses, and builds. Understanding that structure is the fastest way to understand what the company actually does today.

The core product remains what Perplexity itself describes as "an AI answer engine that researches the open web in real time and returns concise, cited answers." Every response includes inline citations, so you can check the source rather than trusting blindly. A long-term G2 reviewer found it works "more like a research assistant than a traditional search engine" — and replaced Google for 95% of daily queries.

The bigger strategic bet is Computer, an agent that acts across your tools and workflows rather than just answering questions. Perplexity says it integrates with 400+ tools and now runs inside Microsoft Teams (following Slack), connecting to Outlook, OneDrive, SharePoint, Excel, and Azure DevOps for background tasks like weekly market scans.

Some eye-catching numbers deserve scrutiny. Perplexity self-reports that Computer has performed $2.8B+ in labor-equivalent work in its first month and that ~92% of C-level executives among paid subscribers use it weekly — claims with no independent verification. A more cautious note comes from practitioners at DigiPix, who caution the output is often surface-level and still needs human proofreading.

Comet extends the same assistant into a full browser, so research and task execution happen where you already work. It completes the shift from "answers about the web" to "working inside the web."

For builders, Perplexity offers:

• Sonar — an API for embedding cited AI search into apps, launched January 2025; Zoom already uses it for an in-meeting assistant (TechCrunch)
• Search API — raw ranked web results, from $1 per 1,000 requests
• Agent API — LLM-generated answers with citations, plus SDKs and a CLI

Notably, Perplexity's own developer docs describe a "Perplexity Search skill" that installs into coding agents — a reminder that agent skills are becoming the connective tissue of this ecosystem. If you want to equip your own agents with skills like this, SkillzBench is building a free directory, security scanning, and benchmarking for exactly that.

Under the hood, Perplexity routes each query across frontier models — OpenAI, Gemini, Claude, and Nvidia are named — so "each question is handled by the model best suited for it." Paid users can also toggle manually between GPT, Claude, Gemini, Grok, or Perplexity's own Sonar models. One caveat: independent testing like PCMag's deep-research comparison found Perplexity fastest (~3 minutes) but shallower than ChatGPT and Gemini, so "best model for the job" remains partly a marketing claim.

What Perplexity Is Good At — and Where It Falls Short

No AI tool earns blind trust, and Perplexity is no exception — its real strengths show up in independent reviews, but so do its limits. Knowing both sides helps you decide where it fits in your workflow.

Independent reviewers consistently rate Perplexity highly for research-heavy work. It holds a 4.5/5 rating on G2, where a reviewer who used it for roughly two years reports replacing Google for "95% of daily queries" and cutting an hour of research down to twenty minutes, according to G2's hands-on review. G2 identifies research-first workflows as the best fit:

• Deep research on complex questions with cited sources
• Product research and feature comparisons
• File and data analysis
• Market research and competitor tracking

For business owners, those strengths translate into concrete use cases. Practitioners point to competitor research, content strategy, customer service chatbots, investment analysis, and CRM-driven workflow automation as areas where Perplexity delivers practical value, as outlined in this business applications guide. Ease of setup scores 97% on G2, and its user base skews toward small business at 70%, so the barrier to entry is low.

Speed is not the same as depth. In PCMag's comparison test, Perplexity's Deep Research produced a report in about three minutes — the fastest of the tools tested — but also the shallowest, with PCMag's reviewer finding it "quite short and lacked the depth" of ChatGPT and Gemini, per PCMag's deep research comparison. That test rested on a single query, so treat it as directional rather than definitive.

The bigger caveat comes from practitioners. DigiPix's own team, despite recommending the tool, cautions that output often stays "at the surface level" and that human research and proofreading remain just as important. Perplexity's marketing claims about "fewer hallucinations" and superior benchmarks are self-reported with no independent verification, and figures like its $2.8B in labor-equivalent work come from the company's own blog.

The practical takeaway: use Perplexity as a fast, cited starting point for research, then verify before acting on anything consequential. If you want to push this workflow further, agent skills — like the "Perplexity Search skill" for coding agents described in Perplexity's own API docs — can automate parts of it; SkillzBench is building a free directory with security scanning, benchmarking, and a free MCP connector to help you discover and test skills like these with confidence.

Putting Perplexity to Work: Pricing, APIs and Agent Skills

Perplexity's pricing is refreshingly simple: the core answer engine is free, while Pro costs $20 per month (or $200 per year), unlocking model toggles and higher usage limits — early 2025 limits gave Pro users 500 Deep Research queries per day versus 5 for free users, though those numbers may have shifted since.

For developers, the company opened up its search stack through APIs. Sonar, launched in January 2025, lets enterprises embed Perplexity's real-time AI search into their own products — Zoom already uses it to power an in-meeting assistant. Pricing starts at $5 per 1,000 searches plus token fees for the base tier, while the newer Fast Search API runs $1.00 per 1,000 requests for raw ranked web results.

What's especially interesting for agent builders is in the API documentation: Perplexity ships a "Perplexity Search skill" that can be installed directly into coding agents, alongside SDKs and a CLI. That means your coding assistant can pull live, cited web results mid-task instead of relying on stale training data.

It's a useful reminder of how quickly agent skills are proliferating — and why vetting matters. Published research found that roughly 26% of agent skills carry at least one vulnerability, so installing a skill blindly into Claude Code, Codex, or Cursor is a genuine security decision, not just a convenience one. That's the gap SkillzBench is being built to close: a free, independent directory that crawls and dedupes skills from GitHub, pins every version to a commit SHA, runs security scans and license checks, and benchmarks each skill in a sandbox to publish its measured Lift in percentage points. A free MCP connector (in development, with the waitlist open) will let you toggle exactly which skills each agent can see.

Before you wire Perplexity's search skill — or any skill — into a production agent, it's worth verifying what you're installing. SkillzBench's trust scores and benchmarks are designed for precisely that, and everything on the platform will be free.

• Pro plan: $20/month or $200/year, with the core search engine free
• Sonar API: $5 per 1,000 searches plus token fees
• Fast Search API: $1.00 per 1,000 requests, returning 10 ranked results by default
• Search skill: installable into coding agents for live, cited web lookups

The takeaway: Perplexity's shift from answer engine to API to installable agent skill mirrors where the whole industry is heading. The tools are getting easier to adopt — the diligence required to adopt them safely is the part that hasn't caught up yet.