PlanOpticon

planopticon / docs / use-cases.md
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3551b80… noreply 1 # Use Cases
3551b80… noreply 2
3551b80… noreply 3 PlanOpticon is built for anyone who needs to turn unstructured content — recordings, documents, notes, web pages — into structured, searchable, actionable knowledge. Here are the most common ways people use it.
3551b80… noreply 4
3551b80… noreply 5 ---
3551b80… noreply 6
3551b80… noreply 7 ## Meeting notes and follow-ups
3551b80… noreply 8
3551b80… noreply 9 **Problem:** You have hours of meeting recordings but no time to rewatch them. Action items get lost, decisions are forgotten, and new team members have no way to catch up.
3551b80… noreply 10
3551b80… noreply 11 **Solution:** Point PlanOpticon at your recordings and get structured transcripts, action items with assignees and deadlines, key decisions, and a knowledge graph linking people to topics.
3551b80… noreply 12
3551b80… noreply 13 ```bash
3551b80… noreply 14 # Analyze a single meeting recording
3551b80… noreply 15 planopticon analyze -i standup-2026-03-07.mp4 -o ./meetings/march-7
3551b80… noreply 16
3551b80… noreply 17 # Process a month of recordings at once
3551b80… noreply 18 planopticon batch -i ./recordings/march -o ./meetings --title "March 2026 Meetings"
3551b80… noreply 19
3551b80… noreply 20 # Query what was decided
3551b80… noreply 21 planopticon query "What decisions were made about the API redesign?"
3551b80… noreply 22
3551b80… noreply 23 # Find all action items assigned to Alice
3551b80… noreply 24 planopticon query "relationships --source Alice"
3551b80… noreply 25 ```
3551b80… noreply 26
3551b80… noreply 27 **What you get:**
3551b80… noreply 28
3551b80… noreply 29 - Full transcript with timestamps and speaker segments
3551b80… noreply 30 - Action items extracted with assignees, deadlines, and context
3551b80… noreply 31 - Key points and decisions highlighted
3551b80… noreply 32 - Knowledge graph connecting people, topics, technologies, and decisions
3551b80… noreply 33 - Markdown report you can share with the team
3551b80… noreply 34
3551b80… noreply 35 **Next steps:** Export to your team's wiki or note system:
3551b80… noreply 36
3551b80… noreply 37 ```bash
3551b80… noreply 38 # Push to GitHub wiki
3551b80… noreply 39 planopticon wiki generate --input ./meetings --output ./wiki
3551b80… noreply 40 planopticon wiki push --input ./wiki --target "github://your-org/your-repo"
3551b80… noreply 41
3551b80… noreply 42 # Export to Obsidian for personal knowledge management
3551b80… noreply 43 planopticon export obsidian --input ./meetings --output ~/Obsidian/Meetings
3551b80… noreply 44 ```
3551b80… noreply 45
3551b80… noreply 46 ---
3551b80… noreply 47
3551b80… noreply 48 ## Research processing
3551b80… noreply 49
3551b80… noreply 50 **Problem:** You're researching a topic across YouTube talks, arXiv papers, blog posts, and podcasts. Information is scattered and hard to cross-reference.
3551b80… noreply 51
3551b80… noreply 52 **Solution:** Ingest everything into a single knowledge graph, then query across all sources.
3551b80… noreply 53
3551b80… noreply 54 ```bash
3551b80… noreply 55 # Ingest a YouTube conference talk
3551b80… noreply 56 planopticon ingest "https://youtube.com/watch?v=..." --output ./research
3551b80… noreply 57
3551b80… noreply 58 # Ingest arXiv papers
3551b80… noreply 59 planopticon ingest "https://arxiv.org/abs/2401.12345" --output ./research
3551b80… noreply 60
3551b80… noreply 61 # Ingest blog posts and documentation
3551b80… noreply 62 planopticon ingest "https://example.com/blog/post" --output ./research
3551b80… noreply 63
3551b80… noreply 64 # Ingest local PDF papers
3551b80… noreply 65 planopticon ingest ./papers/ --output ./research --recursive
3551b80… noreply 66
3551b80… noreply 67 # Now query across everything
3551b80… noreply 68 planopticon query "What approaches to vector search were discussed?"
3551b80… noreply 69 planopticon query "entities --type technology"
3551b80… noreply 70 planopticon query "neighbors TransformerArchitecture"
3551b80… noreply 71 ```
3551b80… noreply 72
3551b80… noreply 73 **What you get:**
3551b80… noreply 74
3551b80… noreply 75 - A unified knowledge graph merging entities across all sources
3551b80… noreply 76 - Cross-references showing where the same concept appears in different sources
3551b80… noreply 77 - Searchable entity index by type (people, technologies, concepts, papers)
3551b80… noreply 78 - Relationship maps showing how ideas connect
3551b80… noreply 79
3551b80… noreply 80 **Go deeper with the companion:**
3551b80… noreply 81
3551b80… noreply 82 ```bash
3551b80… noreply 83 planopticon companion --kb ./research
3551b80… noreply 84 ```
3551b80… noreply 85
3551b80… noreply 86 ```
3551b80… noreply 87 planopticon> What are the main approaches to retrieval-augmented generation?
3551b80… noreply 88 planopticon> /entities --type technology
3551b80… noreply 89 planopticon> /neighbors RAG
3551b80… noreply 90 planopticon> /export obsidian
3551b80… noreply 91 ```
3551b80… noreply 92
3551b80… noreply 93 ---
3551b80… noreply 94
3551b80… noreply 95 ## Knowledge gathering across platforms
3551b80… noreply 96
3551b80… noreply 97 **Problem:** Your team's knowledge is spread across Google Docs, Notion, Obsidian, GitHub wikis, and Apple Notes. There's no single place to search everything.
3551b80… noreply 98
3551b80… noreply 99 **Solution:** Pull from all sources into one knowledge graph.
3551b80… noreply 100
3551b80… noreply 101 ```bash
3551b80… noreply 102 # Authenticate with your platforms
3551b80… noreply 103 planopticon auth google
3551b80… noreply 104 planopticon auth notion
3551b80… noreply 105 planopticon auth github
3551b80… noreply 106
3551b80… noreply 107 # Ingest from Google Workspace
3551b80… noreply 108 planopticon gws ingest --folder-id abc123 --output ./kb --recursive
3551b80… noreply 109
3551b80… noreply 110 # Ingest from Notion
3551b80… noreply 111 planopticon ingest --source notion --output ./kb
3551b80… noreply 112
3551b80… noreply 113 # Ingest from an Obsidian vault
3551b80… noreply 114 planopticon ingest ~/Obsidian/WorkVault --output ./kb --recursive
3551b80… noreply 115
3551b80… noreply 116 # Ingest from GitHub wikis and READMEs
3551b80… noreply 117 planopticon ingest "github://your-org/project-a" --output ./kb
3551b80… noreply 118 planopticon ingest "github://your-org/project-b" --output ./kb
3551b80… noreply 119
3551b80… noreply 120 # Query the unified knowledge base
3551b80… noreply 121 planopticon query stats
3551b80… noreply 122 planopticon query "entities --type person"
3551b80… noreply 123 planopticon query "What do we know about the authentication system?"
3551b80… noreply 124 ```
3551b80… noreply 125
3551b80… noreply 126 **What you get:**
3551b80… noreply 127
3551b80… noreply 128 - Merged knowledge graph with provenance tracking (you can see which source each entity came from)
3551b80… noreply 129 - Deduplicated entities across platforms (same concept mentioned in Notion and Google Docs gets merged)
3551b80… noreply 130 - Full-text search across all ingested content
3551b80… noreply 131 - Relationship maps showing how concepts connect across your organization's documents
3551b80… noreply 132
3551b80… noreply 133 ---
3551b80… noreply 134
3551b80… noreply 135 ## Team onboarding
3551b80… noreply 136
3551b80… noreply 137 **Problem:** New team members spend weeks reading docs, watching recorded meetings, and asking questions to get up to speed.
3551b80… noreply 138
3551b80… noreply 139 **Solution:** Build a knowledge base from existing content and let new people explore it conversationally.
3551b80… noreply 140
3551b80… noreply 141 ```bash
3551b80… noreply 142 # Build the knowledge base from everything
3551b80… noreply 143 planopticon batch -i ./recordings/onboarding -o ./kb --title "Team Onboarding"
3551b80… noreply 144 planopticon ingest ./docs/ --output ./kb --recursive
3551b80… noreply 145 planopticon ingest ./architecture-decisions/ --output ./kb --recursive
3551b80… noreply 146
3551b80… noreply 147 # New team member launches the companion
3551b80… noreply 148 planopticon companion --kb ./kb
3551b80… noreply 149 ```
3551b80… noreply 150
3551b80… noreply 151 ```
3551b80… noreply 152 planopticon> What is the overall architecture of the system?
3551b80… noreply 153 planopticon> Who are the key people on the team?
3551b80… noreply 154 planopticon> /entities --type technology
3551b80… noreply 155 planopticon> What was the rationale for choosing PostgreSQL over MongoDB?
3551b80… noreply 156 planopticon> /neighbors AuthenticationService
3551b80… noreply 157 planopticon> What are the main open issues or risks?
3551b80… noreply 158 ```
3551b80… noreply 159
3551b80… noreply 160 **What you get:**
3551b80… noreply 161
3551b80… noreply 162 - Interactive Q&A over the entire team knowledge base
3551b80… noreply 163 - Entity exploration — browse people, technologies, services, decisions
3551b80… noreply 164 - Relationship navigation — "show me everything connected to the payment system"
3551b80… noreply 165 - No need to rewatch hours of recordings
3551b80… noreply 166
3551b80… noreply 167 ---
3551b80… noreply 168
3551b80… noreply 169 ## Data collection and synthesis
3551b80… noreply 170
3551b80… noreply 171 **Problem:** You need to collect and synthesize information from many sources — customer interviews, competitor analysis, market research — into a coherent picture.
3551b80… noreply 172
3551b80… noreply 173 **Solution:** Batch process recordings and documents, then use the planning agent to generate synthesis artifacts.
3551b80… noreply 174
3551b80… noreply 175 ```bash
3551b80… noreply 176 # Process customer interview recordings
3551b80… noreply 177 planopticon batch -i ./interviews -o ./research --title "Customer Interviews Q1"
3551b80… noreply 178
3551b80… noreply 179 # Ingest competitor documentation
3551b80… noreply 180 planopticon ingest ./competitor-analysis/ --output ./research --recursive
3551b80… noreply 181
3551b80… noreply 182 # Ingest market research PDFs
3551b80… noreply 183 planopticon ingest ./market-reports/ --output ./research --recursive
3551b80… noreply 184
3551b80… noreply 185 # Use the planning agent to synthesize
3551b80… noreply 186 planopticon agent --kb ./research --interactive
3551b80… noreply 187 ```
3551b80… noreply 188
3551b80… noreply 189 ```
3551b80… noreply 190 planopticon> Generate a summary of common customer pain points
3551b80… noreply 191 planopticon> /plan
3551b80… noreply 192 planopticon> /tasks
3551b80… noreply 193 planopticon> /export markdown
3551b80… noreply 194 ```
3551b80… noreply 195
3551b80… noreply 196 **What you get:**
3551b80… noreply 197
3551b80… noreply 198 - Merged knowledge graph across all interviews and documents
3551b80… noreply 199 - Cross-referenced entities showing which customers mentioned which features
3551b80… noreply 200 - Agent-generated project plans, PRDs, and task breakdowns based on the data
3551b80… noreply 201 - Exportable artifacts for sharing with stakeholders
3551b80… noreply 202
3551b80… noreply 203 ---
3551b80… noreply 204
3551b80… noreply 205 ## Content creation from video
3551b80… noreply 206
3551b80… noreply 207 **Problem:** You have video content (lectures, tutorials, webinars) that you want to turn into written documentation, blog posts, or course materials.
3551b80… noreply 208
3551b80… noreply 209 **Solution:** Extract structured knowledge and export it in your preferred format.
3551b80… noreply 210
3551b80… noreply 211 ```bash
3551b80… noreply 212 # Analyze the video
3551b80… noreply 213 planopticon analyze -i webinar-recording.mp4 -o ./content
3551b80… noreply 214
3551b80… noreply 215 # Generate multiple document types (no LLM needed for these)
3551b80… noreply 216 planopticon export markdown --input ./content --output ./docs
3551b80… noreply 217
3551b80… noreply 218 # Export to Obsidian for further editing
3551b80… noreply 219 planopticon export obsidian --input ./content --output ~/Obsidian/Content
3551b80… noreply 220 ```
3551b80… noreply 221
3551b80… noreply 222 **What you get for each video:**
3551b80… noreply 223
3551b80… noreply 224 - Full transcript (JSON, plain text, SRT subtitles)
3551b80… noreply 225 - Extracted diagrams reproduced as Mermaid/SVG/PNG
3551b80… noreply 226 - Charts reproduced with data tables
3551b80… noreply 227 - Knowledge graph of concepts and relationships
3551b80… noreply 228 - 7 types of markdown documents: summary, meeting notes, glossary, relationship map, status report, entity index, CSV data
3551b80… noreply 229
3551b80… noreply 230 ---
3551b80… noreply 231
3551b80… noreply 232 ## Decision tracking over time
3551b80… noreply 233
3551b80… noreply 234 **Problem:** Important decisions are made in meetings but never formally recorded. Months later, nobody remembers why a choice was made.
3551b80… noreply 235
3551b80… noreply 236 **Solution:** Process meeting recordings continuously and query the growing knowledge graph for decisions and their context.
3551b80… noreply 237
3551b80… noreply 238 ```bash
3551b80… noreply 239 # Process each week's recordings
3551b80… noreply 240 planopticon batch -i ./recordings/week-12 -o ./decisions --title "Week 12"
3551b80… noreply 241
3551b80… noreply 242 # The knowledge graph grows over time — entities merge across weeks
3551b80… noreply 243 planopticon query "entities --type goal"
3551b80… noreply 244 planopticon query "entities --type risk"
3551b80… noreply 245 planopticon query "entities --type milestone"
3551b80… noreply 246
3551b80… noreply 247 # Find decisions about a specific topic
3551b80… noreply 248 planopticon query "What was decided about the database migration?"
3551b80… noreply 249
3551b80… noreply 250 # Track risks over time
3551b80… noreply 251 planopticon query "relationships --type risk"
3551b80… noreply 252 ```
3551b80… noreply 253
3551b80… noreply 254 The planning taxonomy automatically classifies entities as goals, requirements, risks, tasks, and milestones — giving you a structured view of project evolution over time.
3551b80… noreply 255
3551b80… noreply 256 ---
3551b80… noreply 257
3551b80… noreply 258 ## Zoom / Teams / Meet integration
3551b80… noreply 259
3551b80… noreply 260 **Problem:** Meeting recordings are sitting in Zoom/Teams/Meet cloud storage. You want to process them without manually downloading each one.
3551b80… noreply 261
3551b80… noreply 262 **Solution:** Authenticate once, list recordings, and process them directly.
3551b80… noreply 263
3551b80… noreply 264 ```bash
3551b80… noreply 265 # Authenticate with your meeting platform
3551b80… noreply 266 planopticon auth zoom
3551b80… noreply 267 # or: planopticon auth microsoft
3551b80… noreply 268 # or: planopticon auth google
3551b80… noreply 269
3551b80… noreply 270 # List recent recordings
3551b80… noreply 271 planopticon recordings zoom-list
3551b80… noreply 272 planopticon recordings teams-list --from 2026-01-01
3551b80… noreply 273 planopticon recordings meet-list --limit 20
3551b80… noreply 274
3551b80… noreply 275 # Process recordings (download + analyze)
3551b80… noreply 276 planopticon analyze -i "zoom://recording-id" -o ./output
3551b80… noreply 277 ```
3551b80… noreply 278
3551b80… noreply 279 **Setup requirements:**
3551b80… noreply 280
3551b80… noreply 281 | Platform | What you need |
3551b80… noreply 282 |----------|--------------|
3551b80… noreply 283 | Zoom | `ZOOM_CLIENT_ID` + `ZOOM_CLIENT_SECRET` (create an OAuth app at marketplace.zoom.us) |
3551b80… noreply 284 | Teams | `MICROSOFT_CLIENT_ID` + `MICROSOFT_CLIENT_SECRET` (register an Azure AD app) |
3551b80… noreply 285 | Meet | `GOOGLE_CLIENT_ID` + `GOOGLE_CLIENT_SECRET` (create OAuth credentials in Google Cloud Console) |
3551b80… noreply 286
3551b80… noreply 287 See the [Authentication guide](guide/authentication.md) for detailed setup instructions.
3551b80… noreply 288
3551b80… noreply 289 ---
3551b80… noreply 290
3551b80… noreply 291 ## Fully offline processing
3551b80… noreply 292
3551b80… noreply 293 **Problem:** You're working with sensitive content that can't leave your network, or you simply don't want to pay for API calls.
3551b80… noreply 294
3551b80… noreply 295 **Solution:** Use Ollama for local AI processing with no external API calls.
3551b80… noreply 296
3551b80… noreply 297 ```bash
3551b80… noreply 298 # Install Ollama and pull models
3551b80… noreply 299 ollama pull llama3.2 # Chat/analysis
3551b80… noreply 300 ollama pull llava # Vision (diagram detection)
3551b80… noreply 301
3551b80… noreply 302 # Install local Whisper for transcription
3551b80… noreply 303 pip install planopticon[gpu]
3551b80… noreply 304
3551b80… noreply 305 # Process entirely offline
3551b80… noreply 306 planopticon analyze -i sensitive-meeting.mp4 -o ./output --provider ollama
3551b80… noreply 307 ```
3551b80… noreply 308
3551b80… noreply 309 PlanOpticon auto-detects Ollama when it's running. If no cloud API keys are configured, it uses Ollama automatically. Pair with local Whisper transcription for a fully air-gapped pipeline.
3551b80… noreply 310
3551b80… noreply 311 ---
3551b80… noreply 312
3551b80… noreply 313 ## Competitive research
3551b80… noreply 314
3551b80… noreply 315 **Problem:** You want to systematically analyze competitor content — conference talks, documentation, blog posts — and identify patterns.
3551b80… noreply 316
3551b80… noreply 317 **Solution:** Ingest competitor content from multiple sources and query for patterns.
3551b80… noreply 318
3551b80… noreply 319 ```bash
3551b80… noreply 320 # Ingest competitor conference talks from YouTube
3551b80… noreply 321 planopticon ingest "https://youtube.com/watch?v=competitor-talk-1" --output ./competitive
3551b80… noreply 322 planopticon ingest "https://youtube.com/watch?v=competitor-talk-2" --output ./competitive
3551b80… noreply 323
3551b80… noreply 324 # Ingest their documentation
3551b80… noreply 325 planopticon ingest "https://competitor.com/docs" --output ./competitive
3551b80… noreply 326
3551b80… noreply 327 # Ingest their GitHub repos
3551b80… noreply 328 planopticon auth github
3551b80… noreply 329 planopticon ingest "github://competitor/main-product" --output ./competitive
3551b80… noreply 330
3551b80… noreply 331 # Analyze patterns
3551b80… noreply 332 planopticon query "entities --type technology"
3551b80… noreply 333 planopticon query "What technologies are competitors investing in?"
3551b80… noreply 334 planopticon companion --kb ./competitive
3551b80… noreply 335 ```
3551b80… noreply 336
3551b80… noreply 337 ```
3551b80… noreply 338 planopticon> What are the common architectural patterns across competitors?
3551b80… noreply 339 planopticon> /entities --type technology
3551b80… noreply 340 planopticon> Which technologies appear most frequently?
3551b80… noreply 341 planopticon> /export markdown
3551b80… noreply 342 ```

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