Cybernetic Taylorism is for you - bookwyrm.ai/blog/genai-f...
#automation #WorkflowAutomation
Cybernetic Taylorism is for you - bookwyrm.ai/blog/genai-f...
#automation #WorkflowAutomation
We'll help map your workflow (automation, enrichment, RAG) & solve a specific data problem. If your use case needs a component we don't have, we'll build it.
Book a call with our CEO, Gavin:
We'll help map your workflow (automation, enrichment, RAG) & solve a specific data problem. If your use case needs a component we don't have, we'll build it.
Book a call with our CEO, Gavin:
Define a Pydantic model (MARC, Dublin Core, or custom), then extract metadata from PDFs/scans in seconds.
Type-safe JSON output, CLI & Python Client based.
bookwyrm.ai/library-automation
Define a Pydantic model (MARC, Dublin Core, or custom), then extract metadata from PDFs/scans in seconds.
Type-safe JSON output, CLI & Python Client based.
bookwyrm.ai/library-automation
Read the docs to see how:
Read the docs to see how:
Achieve bottom-line value from AI. Focus on workflow redesign (not just deploy tools) for back-office automation, invoice processing, and customer service. Get in touch for a free workflow audit workshop.
bookwyrm.ai/consulting
#aiconsulting
Achieve bottom-line value from AI. Focus on workflow redesign (not just deploy tools) for back-office automation, invoice processing, and customer service. Get in touch for a free workflow audit workshop.
bookwyrm.ai/consulting
#aiconsulting
bookwyrm.ai
#agenticworkflow #aidata
bookwyrm.ai
#agenticworkflow #aidata
1. Extract & process docs > phrasal chunks (docs turned into AI-ready data)
2. Index in Pinecone/vector DB
3. Query with cite endpoint > get answers with citations & quality scores
Provide answers grounded in truth.
bookwyrm.ai/reporting
1. Extract & process docs > phrasal chunks (docs turned into AI-ready data)
2. Index in Pinecone/vector DB
3. Query with cite endpoint > get answers with citations & quality scores
Provide answers grounded in truth.
bookwyrm.ai/reporting
LLMs can handle the drudgery, but they get lost easily. They’re not a magic wand, more like an idiot savant.
This framework has turned us into 5x devs 👇
bookwyrm.ai/blog/how-to-...
#AI #Programming
LLMs can handle the drudgery, but they get lost easily. They’re not a magic wand, more like an idiot savant.
This framework has turned us into 5x devs 👇
bookwyrm.ai/blog/how-to-...
#AI #Programming
Stage 1️⃣: `extract-pdf` > `phrasal` (semantic chunking)
Stage 2️⃣: `summarize` (Pydantic models) OR `cite` (source-grounded answers)
No regex, no pre-processing pain. Just clean data > structured output or citations.
bookwyrm.ai
#ai #devs #dataprocessing
Stage 1️⃣: `extract-pdf` > `phrasal` (semantic chunking)
Stage 2️⃣: `summarize` (Pydantic models) OR `cite` (source-grounded answers)
No regex, no pre-processing pain. Just clean data > structured output or citations.
bookwyrm.ai
#ai #devs #dataprocessing
I've been conducting experiments with the use of LLMs for "Design by Contract" (DbC), a paradigm described by Bertrand Meyer. DbC is quite straightforward to use in a language like python (for instance using icontract). The idea is essentially to:
I've been conducting experiments with the use of LLMs for "Design by Contract" (DbC), a paradigm described by Bertrand Meyer. DbC is quite straightforward to use in a language like python (for instance using icontract). The idea is essentially to:
Say it takes 5 minutes to manually input each document.
That's 37.42 days' work.
At €200/day, this costs a business €6,944.
€100 or €6,944?
#cfo #ceo #cto
BookWyrm extracts this collateral and structures it with Pydantic models for OpenAI's ACP. Give ChatGPT the product context it needs to drive sales.
bookwyrm.ai/agentic-commerce
BookWyrm extracts this collateral and structures it with Pydantic models for OpenAI's ACP. Give ChatGPT the product context it needs to drive sales.
bookwyrm.ai/agentic-commerce
They're redesigning workflows.
Here's how to do it:
Analysis > Synthesis > Cybernetic feedback loops.
Measure accuracy vs time saved. Human-in-the-loop architecture.
bookwyrm.ai/blog/genai-for-business
They're redesigning workflows.
Here's how to do it:
Analysis > Synthesis > Cybernetic feedback loops.
Measure accuracy vs time saved. Human-in-the-loop architecture.
bookwyrm.ai/blog/genai-for-business
Extract text from docs > create semantic chunks > structure with Pydantic models > automate workflows.
Type-safe JSON output, source attribution, quality scores. Perfect for invoicing, compliance, data entry.
bookwyrm.ai/backoffice-automation
#ai #dev
Extract text from docs > create semantic chunks > structure with Pydantic models > automate workflows.
Type-safe JSON output, source attribution, quality scores. Perfect for invoicing, compliance, data entry.
bookwyrm.ai/backoffice-automation
#ai #dev
We would love to talk with fellow developers to show off BookWrym and to get your feedback.
Willing to help? Please send us a DM or fill in the form on this page: bookwyrm.ai/contact
#developers
We would love to talk with fellow developers to show off BookWrym and to get your feedback.
Willing to help? Please send us a DM or fill in the form on this page: bookwyrm.ai/contact
#developers
Vibe coding is fun, but how do we verify it? Design by Contract?
We use logical contracts to trust AI software without reading every line: 👇
bookwyrm.ai/blog/contrac...
#AI #SoftwareEngineering #Python #DevCommunity
Vibe coding is fun, but how do we verify it? Design by Contract?
We use logical contracts to trust AI software without reading every line: 👇
bookwyrm.ai/blog/contrac...
#AI #SoftwareEngineering #Python #DevCommunity
Our structured summary endpoint turns PDFs into JSON using Pydantic models to automate mundane tasks like data entry & enrichment.
See some example code here: bookwyrm.ai/ai-workflow-...
Our structured summary endpoint turns PDFs into JSON using Pydantic models to automate mundane tasks like data entry & enrichment.
See some example code here: bookwyrm.ai/ai-workflow-...
We've been testing formatting tricks to fix this. By segregating domain & range into numbers & letters (1. a., 2. b.), we see significantly higher accuracy in element counting and mappings.
bookwyrm.ai/blog/teachin...
We've been testing formatting tricks to fix this. By segregating domain & range into numbers & letters (1. a., 2. b.), we see significantly higher accuracy in element counting and mappings.
bookwyrm.ai/blog/teachin...