An agent walks into a repeat problem like it's the first time, every time. Most memory tools treat everything as disconnected text chunks in a vector store, so nothing carries over, not the reasoning, not the context, not what actually happened last time.
Aperture Nexus is our answer. Context, who, what, when, why, and how, is stamped on every commit, so retrieval actually means something later. Enable lineage tracking when you need it, and every commit traces back to its original source. And because it's built directly on ApertureDB (aperturedata.io), the unified graph-vector-multimodal database already running in production, it works the same whether your agents are text-only today or need images, documents, video, or structured records tomorrow. No migration later if that's where you end up. Knowledge and Memory both live together in ApertureDB.
If you want to see a live demo of how you can use workflows, do join us for our lunch & learn in the morning at 9am PT
https://lu.ma/vnabtolp
@vishakha_gupta4 @hamza_afzal_butt The best part is that what the workflows do is open source. While the workflows on the cloud UI are a subset of possibilities, this repository has the all the detailed workings of workflows under the hood.
With this repository as a reference guide, following are the possibilities:
You may refer to what those scripts are doing to get a blue print for building your own workflow.
You may submit a PR. A PR for any custom workflow would be highly encouraged. TIA.
If it is a general enough workflow, it would eventually get published on the cloud UI too!
@hamza_afzal_butt do join in the lunch & learn happening now - it's one of the things Luis can answer showing how to from the repo as Gautam described : https://lu.ma/vnabtolp
👋 Hey Product Hunt,
We’re kicking off Summer of Workflows — a 12-week series of ApertureDB Multimodal AI Workflows designed to accelerate how developers build their AI agents and GenAI applications with multimodal data.
Release #1 is here: 📥 Croissant Ingestion Workflow — A powerful, ready-to-run workflow that ingests datasets defined using the MLCommons Croissant format directly into ApertureDB.
▶️ Watch the 2-min Demo
🛠️ What it does:
Parses Croissant metadata Downloads referenced assets (images, video, text, etc.)
Ingests them into ApertureDB — keeping structure, attributes, and relationships fully intact
Sets you up for faster AI/ML experimentation, production pipelines, and even RAG agents.
This workflow works out of the box with many datasets hosted by MLCommons, Hugging Face, Kaggle, and other public sources.
💡 Why it matters:
Multimodal data is everywhere — but it’s messy, inconsistent, and scattered. Croissant (by MLCommons) solves the format problem. This workflow solves the ingestion problem.
🔗 Try it now:
→ Run it in the cloud
→ Read the docs
💬 Tell us what you think about this workflow and what you'd like to see us build next. Hit the comments with your ideas—We're listening!
This is just the beginning. One new workflow will launch every Wednesday this summer. Follow along and let us know what you build!
-Team ApertureData
This is a game-changer for AI developers! Congrats on the launch @ApertureDB
@michael_vandi thanks a lot. We are happy to be working with you all!
Hi Product Hunt Community,
You Asked, We Delivered: ApertureDB Cloud Passwordless Login Is Here!
We heard you - it was complicated to setup and login to your ApertureDB instance. You can now use passwordless login to ApertureDB, generate API tokens, and it's particularly easy on ApertureDB Cloud!
No more passwords at instance creation
You no longer need to set or remember passwords when spinning up a new instance. Instead, simply generate a secure access token during setup.
Users can generate secure access tokens directly from the console.
These tokens grant immediate access to the Web UI—no login prompt required.
Tokens are also used to authenticate via the Python SDK and other client tools.
Benefits
Improved developer workflo
API keys can be auto-generated for use in scripts, automation, or third-party services.
Eliminates password reset issues and user lockouts
Reduces credential sprawl across projects
Enables more secure, scalable integration patterns
Consistent experience across UI and API access
Learn more: https://docs.aperturedata.io/Setup/client/configuration
Start your free 30-day trial of ApertureDB today!
Hi Product Hunt,
📢 New ApertureDB Workflow Release Alert!
Summer of Workflows rolls on! We are excited to release MCP Server Workflow — a MCP (Model Context Protocol) server that connects directly to your ApertureDB Cloud instance.
🎬 See It In Action
This workflow gives your Generative AI models and AI agents live, multimodal memory—enabling real-time access to images, text, video, embeddings, and more.
🔍 Why it matters:
Static context limits what AI agents can do. With MCP + ApertureDB, your LLMs can now query fresh, contextual information as they reason, plan, and act.
✅ What’s included:
A deployable MCP-compliant server - Zero glue code needed
Works out-of-the-box with ApertureDB Cloud
Built-in authentication for secure, production-ready deployment
👉 Try ApertureDB MCP Server Workflow
We are building the memory layer for Generative AI. Let us know in the comments what you would build with real-time LLM memory!
Additional Resources
Docs
GitHub Code
@deniece_moxy this is great! Anyone using ApertureDB can easily set up their MCP server for agent memory
Hi Product Hunt,
☀️ Workflow #3 is live! Ingest multimodal data from S3 or GCP Buckets directly into ApertureDB.
This week in our Summer of Workflows Series, we are tackling a core challenge for AI builders: getting real-world multimodal data—images, videos, and more—into a usable format. That’s why we built the Ingest From Bucket Workflow.
What it Does:
This new workflow makes it seamless to ingest data from your AWS S3 or Google Cloud Buckets that you have access to straight into ApertureDB, our multimodal-native vector database. Zero scripts with full control.
🎬 See It In Action
Here’s What You Can Accomplish:
Ingest from S3 or GCP buckets with a single command
Explore your data and metadata in ApertureDB’s unified web interface
Deploy on ApertureDB Cloud with no setup hassle
Perfect For:
GenAI builders
ML teams wrangling real-world datasets
Agentic AI systems that need multimodal data memory
👉 Try It Now! Let us know what you think!
Read the docs | Explore the code
We’re just getting started—this is 3 of 12 in our workflow series.
👀 Come back next week for Release #4!
@deniece_moxy been waiting for this !