AgentHubKnow when to buy, switch, or wait on your AI tool stack.
Workflow stack map
Use Perplexity for web-grounded discovery, NotebookLM when the corpus is fixed, and ChatGPT or Claude when the output must become a clear decision memo.
Decision question
Which stack keeps source evidence visible while moving fast enough to produce a decision memo?
Default roles
Founder, Analyst, Product lead, Operations lead
Last verified
Jun 3, 2026
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Stage-by-stage stack map
Each stage exposes the input artifact, output artifact, recommended tools, and human review timestamp together.
01 / Stage
Does the tool expose enough source trail to trust the first pass?
Reviewed Jun 3, 2026
Input
Research question or buying decision
Output
Source list with initial claims
Perplexity leads when live web discovery is the job; ChatGPT and Gemini matter when discovery is mixed with broader assistant work.
02 / Stage
Is the corpus bounded enough for document-grounded synthesis?
Reviewed Jun 3, 2026
Input
Docs, PDFs, notes, and source extracts
Output
Evidence-backed synthesis
NotebookLM is strongest when the source set is explicit; Notion AI fits teams already storing working notes in Notion.
03 / Stage
Can the tool turn evidence into a recommendation without hiding caveats?
Reviewed Jun 3, 2026
Input
Synthesis and trade-off notes
Output
Recommendation memo with caveats
Use a broad reasoning assistant for the final memo because the artifact must be readable by stakeholders, not just sourced.
04 / Stage
Where will the team revisit this decision when the facts change?
Reviewed Jun 3, 2026
Input
Draft memo and evidence appendix
Output
Shared decision artifact
Notion AI and Glean matter when the memo must remain discoverable in the workspace after the first decision.
Recommended stacks
Each stack shows primary tools, optional tools, cost notes, and overlap warnings together.
Teams that need source visibility before they trust recommendations
Primary
Separate live discovery from fixed-corpus synthesis, then draft the memo with a stronger writing assistant.
Cost signal
Avoid paying for every broad assistant if research seats only need source-backed discovery.
Published paid monthly starting point for Perplexity: about $20/seat/mo.
Stack economics
This panel uses published self-serve pricing only. Quote-only and usage-credit gaps stay visible as caveats, and deeper pairwise math opens in the calculator.
Default team size
10
Monthly estimate
$600
Change impact score
95
Decision artifact
Save a stack with the default team context into the local watchlist, then copy a decision memo that includes current change impact.
Shortlist actions
Use these links when the ranking or use-case page already narrowed the field and you want to check pricing or open the best direct compare next.
Watchlist
Save the stack, monitor buying-impact changes, and turn the result into a decision memo.
Evidence layer
The workflow page frames the decision; the deeper evidence still lives in AgentHub's existing decision intelligence pages.
Compare
ChatGPT vs Claude
Compare
ChatGPT vs Perplexity
Compare
Perplexity vs NotebookLM
Pricing
ChatGPT pricing guide
Pricing
NotebookLM pricing guide
Pricing
Perplexity pricing guide
Alternatives
NotebookLM alternatives
Alternatives
Perplexity alternatives
Use case
AI research tools for individual analysts: fit guide
Use case
AI research tools for team workflows: comparison and fit guide
Best
ai-research-assistants
Best
research-assistants
Alert rules
Workflow alerts distinguish price, plan, governance, overlap, fit delta, and memo refresh impact.
fit-delta / medium
Refresh saved memos when a source-grounded research tool changes enough to affect evidence confidence.
FAQ
These answers stay close to the pricing, rollout, and fit questions that come up most often during evaluation.