AI & RAG

Index Dropbox sales collateral into a searchable knowledge base

Watches a Dropbox sales-collateral folder, extracts text from new or changed files, embeds the chunks with OpenAI, and stores them in Postgres so reps can query them later.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDropbox collateral file added or changedDropboxDropbox
  • ActionDownload file and extract textDropboxDropbox
  • LogicChunk text and skip unchanged files by hash
  • ActionGenerate embeddings for each chunkOpenAI
  • OutputUpsert chunks and vectors into PostgresPostgreSQLPostgres

What it does

Keeps a retrieval index in sync with your Dropbox sales-collateral folder. Whenever a deck, one-pager, or case study is added or updated, it pulls the file, splits it into passages, generates embeddings, and upserts them into a Postgres vector table that downstream answer bots read from.

When to use it

Run this as the foundation step before any rep-facing retrieval bot. Marketing and sales-enablement teams who drop fresh collateral into Dropbox want it searchable within minutes, without anyone manually re-uploading content into a separate tool.

How it works

  1. 1A Dropbox change on the collateral folder triggers the run with the affected file path.
  2. 2The file is downloaded and its text is extracted (PDF, DOCX, slides).
  3. 3A logic step splits the text into overlapping chunks and skips files that are unchanged by hash.
  4. 4OpenAI generates an embedding for each chunk.
  5. 5The chunks and vectors are upserted into Postgres, keyed by file path so re-indexing replaces stale rows.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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