A research assistant with web search and citations combines the speed of on-device AI with optional internet access to find and verify answers offline. MyBenAI routes web searches through Serper (or falls back to DuckDuckGo), caches results locally for 30 days, and uses multi-agent summarization to synthesize sources into cited, fact-checked answers—all under your control.
How Multi-Agent Research Works
Research is rarely a single task. You need someone to find sources, someone to verify claims, and someone to synthesize everything into a coherent answer. MyBenAI does this with sub-agents that work in parallel and then collaborate on the result.
When you ask a research question, MyBenAI deploys multiple specialized agents:
- Researcher agent: Searches for relevant sources (local knowledge, documents, optional web search) and retrieves information related to your query.
- Fact-checker agent: Reviews the sources found by the researcher and flags inconsistencies or unverified claims.
- Summarizer agent: Synthesizes the findings into a cohesive answer, preserving citations and highlighting consensus vs. disagreement.
- Document analyst (optional): If you've loaded PDFs or notes, this agent retrieves and analyzes relevant content from your personal documents.
These agents run in parallel for speed, but they serialize their LLM calls (decode on a global mutex) to avoid overwhelming your device. The result: thorough research completed faster than a single AI could do it, with built-in verification and cross-checking. Learn more about how sub-agents speed up research on your phone.
Adding Web Search: Serper to DuckDuckGo Fallback
On-device AI has knowledge from training data, but that knowledge has an expiration date. For current events, recent research, or factual information that changes (stock prices, weather patterns, newly published studies), you need live web search. MyBenAI makes this optional and transparent.
You control whether web search is enabled. If you enable it, you supply your own Serper API key (a free tier exists; paid tiers are inexpensive). Your search queries go to Serper, which returns results quickly. If Serper is unavailable or you have no key, MyBenAI automatically falls back to DuckDuckGo at no cost. This means research doesn't stall: you always get an answer, either from Serper or the fallback.
The search is optional per request, too. You can ask MyBenAI to research locally only, or to include web search. This gives you fine-grained control: for topics where local knowledge suffices, skip the network call and save time. For current events or niche topics, enable search.
The 30-Day Local Cache Strategy
Every web search result MyBenAI fetches is cached locally for 30 days. This serves multiple purposes. First, it saves bandwidth and API costs: if you ask similar questions within 30 days, the cache is hit instead of making a new Serper call. Second, it creates offline continuity: you can research the same topic offline after the initial search by reading cached results. Third, it preserves provenance: you can review what sources were found and when.
The cache respects freshness. If you explicitly request a new search, the cache is bypassed and fresh results are fetched. If you revisit a cached result after 30 days, it expires and a new search is made. This balance between speed and currency means you get fast, fresh answers without redundant API calls.
Citations and Source Verification
Research is only credible if you know where information came from. MyBenAI automatically tracks sources and generates numbered citations. When the researcher agent pulls a fact, that fact is tagged with its source (URL, document name, PDF page number). When the summarizer synthesizes an answer, it preserves these citations.
In the final answer you read, claims are marked with citation numbers: "According to research, the Eiffel Tower is 330 meters tall [1]." You can tap or click the [1] to see the source: a URL cached from a web search, or a page reference to a PDF you uploaded. This makes research transparent and verifiable. You're not trusting a single LLM's reasoning; you're reading a synthesized answer grounded in sources you can inspect.
Battery and Time Limits: Keeping Research Efficient
Mobile devices have finite battery and compute resources. Multi-agent research can be intensive, so MyBenAI caps it intelligently. When you're charging, up to 4 agents can run in parallel. When you're unplugged and the battery is low, the fan-out is reduced to 0 agents (research falls back to a single pass). In between, the limit scales with battery state. This prevents research from draining your phone to 5%.
Each agent also has a 90-second timeout. If the researcher or fact-checker can't find an answer in 90 seconds, it stops and returns what it has. The summarizer then works with partial information rather than hanging indefinitely. This ensures research completes in reasonable time, especially on slower network connections.
Research Workflows: From Question to Cited Answer
Here's a real research workflow using MyBenAI's research assistant:
Scenario: You're writing an article about the history of TypeScript. You ask: "When was TypeScript released and what were the main design goals?"
What happens: The researcher agent searches your local documents (if any) and optionally queries the web. It finds information about TypeScript's 2012 release and its design principles. The fact-checker agent cross-checks this: "Microsoft released TypeScript in 2012 as a typed superset of JavaScript. Goals included static typing, better tooling, and scalability." The summarizer synthesizes: "TypeScript was released by Microsoft in October 2012. Its three main design goals were: (1) providing optional static typing for JavaScript; (2) enabling IDE support and tooling that's robust for large codebases; and (3) allowing gradual adoption, so teams could migrate incrementally [1, 2]. In the same year, version 0.8 was released, and adoption grew in enterprise settings [1]." Citations point to the web search results cached from Microsoft's blog and TypeScript's GitHub history.
Result: An answer grounded in sources, fact-checked by multiple agents, and cached locally so you can revisit it offline without a new search.
Complete Control: Optional and User-Driven
The entire system is optional. You can disable web search entirely and rely on local knowledge only. You can disable the fact-checker if you want speed over verification. You can ask a question with manual settings: "Research only from my documents, no web search, 1 agent, fast mode." Or you can let MyBenAI choose sensible defaults. You can review every agent's findings in the research log and see which sources were used and how long each step took.
This transparency and control are core to the design. You're not trusting a black box; you're directing researchers that work for you. You can audit, adjust, and repeat.
When Local Knowledge Isn't Enough
Here's the honest trade-off: a 0.6B to 8B local model is weaker than GPT-5 or Claude at hard reasoning, multi-step logic, and niche expertise. If you're researching quantum mechanics or advanced economics, a small local model may struggle even with sources. In those cases, web search helps by providing expert-written sources, which the local model reads and summarizes rather than reasoning from scratch. The model's role becomes synthesis, not reasoning, and that's where small models excel.
Also, web search gives you live knowledge. Without it, your AI's knowledge is frozen at training time. For anything that changes (news, research papers, product updates), optional web search is essential. That's why it's built in and optional: you choose when the trade-off is worth a network request.
Practical Uses for Cited Research
Students use this to write papers with sources: load textbooks and lecture notes, let the research assistant synthesize answers with citations, and export the result with references. Writers use it to fact-check claims while drafting. Professionals use it for market research, competitive analysis, and technical due diligence, all without uploading proprietary information to a cloud service. Researchers use it to explore topics by cross-referencing local documents and web sources in one place.
Because everything is optional and user-controlled, you can customize the research process to your needs. Quick fact-check? Disable the fact-checker for speed. Deep investigation? Enable all agents and wait for consensus. Sensitive topic? Disable web search and rely on local documents only.
Getting Started with Cited Research
MyBenAI's research assistant is built-in, ready to use. Start by asking a research question in chat. If you want web search, enable it in settings and add a Serper API key (free tier available). Load your documents into MyBenAI if you have reference material. Then ask your questions, and let the agents do the work. Citations appear automatically, and results are cached locally so you can revisit them offline.
Ready to research smarter? Download MyBenAI for $2, a one-time purchase. Learn how function calling and tools power research assistants, explore how the summarizer synthesizes multi-source findings, or read about web search, caching, and offline citations in detail.