Why Real-Time AI Search Matters
TLDR: Perplexity has released Sonar, an API that delivers real-time answers from the live web with citations. Most AI tools reply from outdated training data, which is a problem for organisations that depend on current information. Real-time search matters because it reduces manual research, improves accuracy and gives teams faster, grounded answers inside the tools they already use.
What Sonar Does
Sonar is Perplexity’s new API for fast, grounded search. It connects directly to the live web, runs real-time checks and returns answers with citations. Most AI systems rely on training data that may be months old. Sonar avoids that limitation by retrieving information as it exists today.
There are two versions:
- A base model for quick questions.
- A Pro model for complex, multi-step queries that need deeper checking and more citations.
The benefit is simple : You get fast, factual responses you can verify.
Why Real-Time Search Matters in AI
Static AI answers are fine for general knowledge. They fail when the information changes daily: regulations, product updates, competitor activity, pricing movements or anything time-sensitive.
Sonar gives teams access to up-to-date results without switching tools, tabs or workflows.
For non-technical teams, this removes two common issues:
- slow, manual searching
- uncertainty about whether the information is current
Real-time search also reduces reliance on guesswork or outdated assumptions that often appear in general AI assistants. Because Sonar provides citations, staff can check the source directly rather than trusting an unverified summary.
How Sonar Works Inside a Workflow
Sonar runs a live search based on a question, evaluates results and produces a short, sourced answer. The Pro version breaks down harder questions into multiple searches and consolidates the findings.
Developers can restrict Sonar to approved sources so it stays inside responsible boundaries. This matters for organisations that can’t rely on the open internet for sensitive queries.
Sonar also supports large inputs. Teams can ask about long documents, multi-part topics or a mix of internal notes and external information.
It is accessed through an API, which means it can be embedded directly into existing systems. No new interface. No new tools for staff to learn.
Where You Feel the Value
Real-time search removes repetitive tasks that take time away from actual work.
Teams get immediate value in areas like:
- basic fact-checking
- understanding new developments
- checking recent news
- validating claims
- pulling current competitor information
- answering customer questions accurately
Internal chatbots also become more useful when answers include citations instead of assumptions. Customer support, sales and operations can all benefit from this shift.
The value is pretty practical: fewer manual searches, fewer mistakes and less time spent cross-checking information.
How Sonar Fits Early AI Adoption
Sonar is an example of the kind of AI tool organisations can adopt early without creating complexity.
You don’t need a custom model.
You don’t need a data science team.
You don’t need an AI strategy with dozens of workstreams.
You need:
- a simple integration
- clear internal guidelines
- approved sources
- a basic review process for higher-risk use
Real-time search is exactly the type of tool that helps non-technical organisations gain confidence with AI because it solves a familiar problem in a low-risk way. It replaces slow research, not judgment. It provides current information, not assumptions. It strengthens decisions by grounding them in evidence.
How Much Is it?
The base version uses a lightweight model designed for speed and cost control.
Pricing is fixed per thousand searches with low input and output costs. Sonar Pro costs more because it handles deeper queries, runs additional searches and returns more citations.
For teams that currently rely on manual research or expensive external tools, predictable usage-based pricing is easier to budget for. This keeps the cost of factual retrieval aligned to operational needs.
Real-time AI search is not about sophistication. It is about reliability. When teams can access current information with citations:
- decisions become more grounded
- work speeds up
- errors reduce
- staff confidence increases
- reliance on outdated sources drops
Sonar shows a practical path forward:
- AI adoption begins with tools that remove friction from everyday tasks, not tools that require advanced knowledge.
- For organisations just starting, this category — real-time factual search — is one of the safest and most useful entry points.
FAQs
Q: Can real-time search replace our internal knowledge base?
A: No. It complements it. Internal knowledge needs its own system. Sonar handles external information.
Q: Does Sonar handle sensitive data?
A: Only if you restrict the sources. It is designed to use approved inputs when configured that way.
Q: Can we use Sonar for regulatory or legal checking?
A: It can help surface current information, but decisions still require the appropriate internal review.
Q: How much technical work is required to integrate it?
A: Minimal. A developer can connect the API, and teams use it through existing tools.
Q: Does real-time search solve hallucination issues?
A: It reduces them significantly because answers come from current sources with citations.
Q: Is this suitable for small teams?
A: Yes. It removes manual searching, which is often where small teams lose the most time.
If your organisation wants to explore AI tools like real-time search in a safe, structured way, the AI 5-Day Bootcamp gives non-technical teams the foundations to evaluate and adopt tools like Sonar without confusion or risk.