Research team using an AI agent to monitor industry news
The AI employee searches the web in real time and surfaces relevant updates. No manual scanning required.
Web Search
Every AI employee can search the live internet for current information and answer with sources, no setup required. It runs automatically whenever the employee needs something it does not already know, such as a competitor update, a price, or a recent news item. Results are cited titles, snippets, and URLs, synthesized into a plain answer inside the chat.
Your employee has access to the live internet. Ask it to research competitors, find industry benchmarks, look up regulatory changes, or verify a claim, and it searches the web in real time. It does not rely on stale training data. It finds current information from current sources.
The difference from a regular search engine is what happens after the results come back. Your employee reads every page, filters out noise, extracts the relevant data points, and synthesizes a summary tailored to your question. Ask "what are competitors charging for similar products?" and you get a structured comparison table with sources, not 10 blue links.
Web search integrates with every other capability. Your employee can search for information, then use it to write a report, update a spreadsheet, draft an email, or create a presentation. The research feeds directly into the work, with no copy-paste step in between.
A single search comes back as a set of real results: the page title, the link, and a snippet of the text on it. Your employee chooses how many to pull, usually a handful, and can run several searches inside one task when the first set does not settle the question. It reads what came back, discards what is irrelevant, and keeps only the pieces that answer you. The sources travel with the answer, so you can click through and check anything yourself.
Search finds the page, and sometimes you need the whole page. When a snippet is not enough, your employee pairs the search with web scraping to pull the full text of a specific address and works from that instead. Together the two cover the normal shape of research: find the candidates, read the ones that matter, write up what they actually say.
There is nothing to install and nothing to connect. Every employee can search from the day you hire it, on whatever channel you happen to be using, including email, a connected messaging app, or a routine running overnight while you sleep. Each search is a small metered action recorded in the activity log, so you can always see when your employee went looking and what it was looking for.
Live Web Search Built Into Every Task
Sistava gives your AI employee the ability to search the web in real time as part of any task. When the agent needs current information, market data, recent news, or any fact it does not already know, it runs a live search and reads the results before responding.
This is a fundamental upgrade over AI models trained on a fixed knowledge cutoff. Your AI agent works with fresh information, not a snapshot from months ago. If something happened recently, it can find out.
Synthesized Answers with Sources, Not a List of Links
After searching, the agent reads the relevant results and synthesizes a coherent answer grounded in what it found. You get an intelligent summary with cited sources, not a raw list of URLs to click through yourself.
This is what makes web search genuinely useful in a workflow context. When an AI employee researches a competitor, vets a vendor, or looks up regulatory requirements, it delivers a usable briefing, not a search results page.
Research That Feeds Directly Into Execution
Because web search is a tool the agent uses autonomously, research outputs can feed directly into the next step of a task. An agent drafting a market analysis can search for current data, pull the key numbers, and incorporate them into the document, all in one workflow.
There is no copy-pasting between a search tab and a document. The agent handles the full chain: search, read, extract, synthesize, use. This collapses multi-step research tasks into a single delegated instruction.
How It Works
Your AI agents search the live web during any task and return synthesized answers drawn from current sources, not stale training data.
When a task requires current information, your AI employee runs a web search automatically. It does not dump raw links into the response. It reads the results, filters out low-quality sources, and synthesizes a direct answer with citations. Competitor pricing, recent news, product documentation updates, regulatory changes. The agent pulls what is relevant and applies it in context.
Web search runs inline with the agent's reasoning, not as a separate step you have to trigger. If the agent is drafting a competitive analysis and spots a gap in its knowledge, it searches to fill it. Multiple searches can run in a single task. The agent treats the live web as a tool it calls when needed, the same way it would call any other capability in its toolkit.
Because search is built in rather than bolted on, there is no setup step between hiring an employee and getting a researched answer out of it. Each result carries its title, its link, and the snippet the employee read, so the trail back to the original page is always intact. When a snippet is too thin to be useful, the employee pairs the search with web scraping and reads the page in full instead of guessing at the rest.
Use Cases
Sales team equipping an AI agent with live competitive intelligence
The agent searches for current competitor information before every major touchpoint. Always up to date.
Support team helping an AI employee answer questions about recent updates
When the knowledge base doesn't have the answer, the agent searches the web and uses the latest information.
Content team using an AI agent to fact-check before publishing
The AI employee verifies claims against current web sources in real time. No outdated information goes out.
Comparison
| Before | After |
|---|---|
| AI agents are limited to their training data, which is always out of date. | Web search gives the AI employee access to current information in real time. |
| Researching a topic means doing it yourself and pasting it in. | The agent searches autonomously and incorporates what it finds. |
| Answers are wrong when the world has changed since training. | Live web search keeps the AI employee grounded in current reality. |
| Monitoring the web manually takes hours every week. | The AI agent searches on demand and surfaces what matters. |
FAQ
Does the AI agent search the web automatically, or does it need to be told to?
The agent decides when to run a web search based on the task. If it needs current information it does not already have, it will search. You can also explicitly ask it to research something, and it will search accordingly.
Does the agent cite its sources when it uses web search?
Yes. When the agent uses web search to answer a question or complete a task, it includes the sources it consulted in its response. You can verify the information directly from the original URLs.
Can the AI employee search for real-time data like stock prices or news?
Yes. Web search returns live results, so your agent can access current news, prices, market data, and any publicly available information. The freshness of results depends on what is indexed and available on the web at search time.
Is web search included in all plans?
Web search is available as a utility tool that can be enabled for any AI employee. Check your plan details for usage limits. Each search query counts against your usage allocation.
Can my AI agent look up current information from the web during a conversation?
Yes. The live web search tool lets your AI employee fetch real-time results from the internet mid-task, so it is not limited to its training data. Search results feed directly into its responses.
Do I need to turn web search on for each AI employee?
No. Web search is built into every AI employee from the moment you hire it, so there is no API key to paste, no account to create, and no connection to keep alive. It works the same on every channel, including chat, email, and a routine that runs while you are away.
How many results does one web search bring back?
A web search returns a handful of results by default, each with the page title, the link, and a snippet of the text, and the employee can ask for more when a topic needs wider coverage. It can also run several searches inside a single task, narrowing the query each time until it has what it needs.
Can my AI employee read a full article instead of just the search snippet?
Yes. Web search finds the page and the separate web scraping capability pulls the full text of that page, so your employee can read an entire article, pricing table, or documentation page rather than working from a two line summary. It decides which pages are worth opening in full based on what you asked for.
My research agent now pulls competitor updates automatically before every weekly briefing. I stopped manually checking five sites every Monday.
Where Web Search fits
Web Search is part of Things they can do out of the box.
Every AI employee ships with built-in abilities that work out of the box. Search the live web for real-time information, scrape and crawl any website for structured data, and generate images directly in conversation. No plugins to install, no APIs to configure.
- Things they can do out of the box: Research, create, and extract without plugins.
Read the guide
More in Capabilities
- Web Scraping: Give any employee a URL and they read the full page: article, blog post, documentation, competitor page, pricing table, whatever is public. They return clean text with the ads, navigation, and boilerplate stripped out, ready to summarize, compare, or act on. It is enabled for every employee at hire, costs no credits, and works on JavaScript-heavy pages without any setup on your side.
- Image Generation: Ask any employee to create an image and it builds a detailed prompt, generates it with an OpenAI image model, and saves the result to Drive with a persistent link. Use it for logos, social graphics, illustrations, diagrams, or landing page visuals, described in plain language. No setup required: every employee can generate images at hire, with a Model, Quality, and Shape default you can adjust per tool.
- Code Interpreter: Code Interpreter is on our roadmap: a sandboxed Python environment your AI employee will use to run scripts, crunch numbers, and transform data files on request. Instead of describing a calculation in words, you'll be able to ask for the actual computation and get back a checked result, not a guess. It is not available yet.
- Video: Hand your employee a prompt and get back a short, ready-to-post video clip, filed straight into your Drive. Built for social cuts, ad concepts, and quick product demos. Editing your own footage is coming next.
- B2B Marketplace: A network of real, vetted businesses living inside Sistava. Ask any AI employee to find a vendor, a partner, or a service provider, and it checks this network first, before it ever touches the open internet. Get listed yourself and the same network works the other way: visitors, customers, and other businesses' AI employees can discover and recommend you.
- Document Editor: Ask an employee for a spreadsheet, a report, a slide deck, or a data export, and get back a real .xlsx, .docx, .pptx, .csv, or .pdf file, not a wall of text pasted into chat. It can also revise a file you already gave it through the same chat-and-Drive workflow, keeping the work you did not ask to change intact whenever the format supports it. For PowerPoint, it can turn a brief into native slides with layouts, charts, images, shapes, tables, and speaker notes. PDFs can be polished reports or colorful, fully designed pages with professional print typography. Included with every employee on every plan, nothing extra to connect or unlock.
- Premium Prospect Database: Find real people to sell to and reveal their verified work email and phone, pulled from a premium database of over a billion professionals worldwide. Filter by role, seniority, industry, company size, and location to build a targeted list, then have your employee save the best prospects straight into your CRM. A premium add-on on paid plans; on the free plan your employee researches prospects on the open web.
- Send an Employee to Your Meeting: Share a Google Meet, Zoom, or Microsoft Teams link and your employee joins the call as a named participant. It listens, keeps a full speaker-tagged transcript, and speaks up out loud when you address it by name. When the call ends, the transcript lands in Drive and a summary shows up in chat.
- Get a Live Meeting Transcript: Your AI employee joins a Google Meet, Zoom, or Microsoft Teams call and captures a full transcript as people speak, tagged by speaker and timestamped. Ask for it mid-call, ask for it after, or just ask what someone said ten minutes ago. When the meeting ends the transcript is saved to your employee's Drive automatically.
- Meeting Summary: When a meeting your employee attended ends, it writes a summary and drops it in chat automatically: what got decided, who owns what, and the action items. No need to ask for a recap, it is already waiting when you check in.
- Document Text Extraction: When you attach a document to a chat message or upload it for training, your employee turns it into readable text on its own. PDFs, Word, Excel, and PowerPoint files, OpenDocument files, RTF, and plain text or data files all come through automatically, tables included, with no conversion step for you to run first.
- Import a Skill from GitHub or a URL: Paste a link to a GitHub repository or a URL that hosts an Anthropic-style Skill package, and your employee will import the whole thing directly instead of you rebuilding it by hand in the Create Skill drawer. This is on our roadmap and is not active yet: the option appears in the Skills toolbar and in the Create Skill drawer today, but importing does not run until we ship it.