How to Automate Research With AI
AI research goes wrong when it is treated as a single question rather than a pipeline. A working research system has four stages — gather sources, extract and structure claims, synthesise across them, and produce an output someone can act on — with the model doing the extraction and synthesis while tooling handles retrieval and storage. That separation is what makes results repeatable and checkable against sources. This guide collects the research material on Onexial in build order: the concepts behind deep research and retrieval, the workflows that run weekly briefs and market reports, the stacks that support them, the prompts that do the synthesis, and the use cases showing what the output looks like in practice.
Core concepts behind Research
Before wiring anything together, the vocabulary has to be precise. These 3 definitions cover the terms that show up in almost every Research discussion — each one links to a full entry with an example and its own connections inside the graph.
Deep Research (AI)
Long-running AI research task that produces a cited multi-page report.
Research Automation
Research automation turns a question into a sourced, structured answer using search, retrieval, extraction and synthesis agents.
On-chain Data
On-chain data is the public record of every transaction, balance and contract call — the raw material for wallet tracking and market research.
Workflows: how Research runs end to end
Concepts only matter once they become a repeatable process. Below are 8 documented workflows that apply Research to a concrete problem, with the steps, the tools involved and the variations worth testing.
Personal Research Assistant Workflow
A repeatable system to research any topic deeply in under 30 minutes.
AI Market Research Report in One Afternoon
From blank page to sourced, structured 20-page market report in ~4 hours.
Turn Deep Research Into a Weekly Executive Brief
Use an AI Deep Research agent every Monday to produce a cited market brief in 20 minutes.
Build a Research Automation Pipeline
Question in, sourced structured brief out — on a schedule.
AI Crypto Research Workflow
A repeatable research loop: turn a question into market data, on-chain evidence and a written risk view before any position is considered.
AI Token Research Workflow
Screen a token in under 30 minutes: contract facts, liquidity structure, holder concentration and a written risk verdict.
DeFi Yield Research Workflow
Evaluate a yield opportunity by decomposing where the return comes from and what has to break for it to disappear.
Analyze A Wallet With AI
Turn a raw transaction history into a readable profile: strategy, holding periods, risk behaviour and realised performance.
The Research tool stack
A stack is a set of tools chosen for one job, not a list of favourites. These 5 stacks show which combinations hold up in production for Research, and what each layer is actually responsible for.
AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
Solo Market Researcher Stack
One person running weekly market intel across 20+ companies.
Research Automation Stack
Search, fetch, extract and synthesise sourced briefs on a schedule.
AI Crypto Research Stack
A read-only research stack combining an AI assistant, web search, market data and on-chain analytics to screen assets quickly.
On-chain Research Stack
Explorer, indexer and analytics layers combined so wallet and token questions get answered with verifiable data.
Trade-offs and comparisons
Most Research decisions are trade-offs rather than right answers. These 2 comparisons break down the real differences, when each option wins, and the recommendation for the common case.
On-chain Data vs Exchange Data
On-chain data shows verifiable wallet-level behaviour; exchange data shows aggregate price discovery. Serious research needs both.
AI Research vs Traditional Research
AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.
Prompts you can reuse
Prompts are reusable components. Each of these 12 prompts is written to be dropped into a Research workflow with minimal editing, including the context it expects and an example output.
Market Research Synthesizer
Compress 10-20 sources into a 1-page decision-grade brief.
Competitor Teardown Prompt
Deep-dive one competitor from public artifacts.
Deep Research Prompt Template
Reusable Deep Research prompt that produces cited, structured reports every time.
Sourced Research Brief Prompt
Produces a structured brief where every claim carries a citation.
Token Research Prompt
Structures a full token due-diligence pass: mechanics, liquidity, concentration, bear case and unverifiable claims flagged explicitly.
Crypto Market Analysis Prompt
Produces a structured market brief: regime, liquidity conditions, sector rotation, catalysts and what would change the view.
Crypto Portfolio Analysis Prompt
Audits a portfolio for hidden concentration, correlated exposure, custody risk and missing exit plans.
Wallet Analysis Prompt
Turns a transaction export into a behavioural profile: strategy type, timeframes, risk pattern and whether the wallet is worth watching.
Smart Money Analysis Prompt
Tests whether a group of 'smart money' wallets is genuinely informative or a survivorship-biased label.
DeFi Protocol Research Prompt
Decomposes a protocol's yield source, contract risk, oracle dependency and exit path into a written risk verdict.
Yield Comparison Prompt
Compares yield opportunities on a risk-adjusted basis instead of ranking them by advertised APY.
Crypto Research Agent Prompt
System prompt for a research agent that must cite sources, separate fact from inference, and refuse to predict prices.
Real applications of Research
Finally, 7 applied use cases: the situation, the system used to solve it, and the outcome. This is the layer that turns Research from an idea into leverage.
Tech Creator Replaces a Research Assistant With a Workflow
A YouTuber cut their research time per video from 8 hours to 90 minutes.
Consultancy Automates Weekly Market Scans
A sourced competitor and market diff replaced a manual research day.
Find Smart Money Activity
A research group verified 40 leaderboard wallets and kept only 11, turning a noisy signal source into a usable research queue.
Research A Token With AI
A structured AI research pass cut token screening from three hours to 35 minutes and produced documented passes instead of impulse entries.
Build An AI Crypto Research Agent
A read-only research agent produced daily briefings on a 30-token watchlist, cutting a 90-minute manual routine to a 10-minute review.
Analyze Wallets With AI
AI profiling of 60 candidate wallets cut a week of manual review to an afternoon and identified 4 worth monitoring.
Discover DeFi Opportunities
Ranking yields by real fee-based return instead of advertised APY moved capital from a 31% headline position to an 8.4% sustainable one.
Frequently asked questions
- What does the Personal Research Assistant Workflow workflow do?
- Standardize a query → harvest → cluster → synthesize loop so every research session ends with a structured brief.
- What problem does Personal Research Assistant Workflow solve?
- Reading 20 tabs and stitching notes manually wastes hours and rarely produces a usable synthesis.
- How many steps does Personal Research Assistant Workflow take?
- 5 steps. It starts with write a single research question and 5 sub-questions. and ends with save the brief into your second brain with backlinks..
- Which tools does Personal Research Assistant Workflow need?
- It uses agent-research-stack, content-creator-stack — each linked below with its own node.
- What is the AI Research & Knowledge Stack stack for?
- Search, capture, structure and synthesize information faster than you can read it.
- Which tools are in this stack?
- Perplexity or Exa (web research), Lovable AI Gateway (synthesis + structured output), Notion or Obsidian (knowledge base), Readwise (highlight capture), Make (capture → enrichment → DB pipeline).
- Are there alternatives to this stack?
- Yes — ChatGPT Pro with browsing for a one-tool baseline.
- What is the Tech Creator Replaces a Research Assistant With a Workflow use case?
- Deep-dive videos required a part-time researcher the channel could no longer afford between sponsorships.