Gmeow, Cats!
We’re excited to share the latest update on what we’ve been building at Replicats!
As you may know, our objective with Replicats is to offer the ultimate tool to assist users in navigating the market noise by democratizing access to advanced AI investment managers. Through our platform, anyone connected to the internet can make financial decisions without the weight of emotional burdens using a highly customizable Agent. As capital markets work 24/7 and are moving onchain, we believe anyone, regardless of location, should be able to access and invest in crypto and Real-World assets like stocks, forex, and indexes without hassle.
To get closer to that vision, we launched several core components of our platform that are steadily bringing us closer to the main vision of Replicats as your go-to solution for AI-powered financial management. However, Sprint #2 wasn’t just about technology; our team is also evolving.
We’re proud to welcome Magdalena Pire Schmidt as Replicats’ first COO. With leadership experience at Google, Visa, and Adyen, she brings a sharp eye for scale and execution. We’ve also expanded our tech team with one new developer and another quant trader, helping us move more rapidly tech-wise.
We are also proud to announce that our Dashboard was finally open to our Early Beta Testers.
You can find out how to test it here.
Next week, we will update our Documentation with Sprint #3. But for now, let's review what we accomplished this cycle. We hope you enjoy this reading and keep in touch with us on our social media and community channels.
- Bernardo, Guto, and the Replicats Team
Operational dashboard for internal and external use.
Onboarding of the first Early testers
Develop External Dashboard (Replicat One) for early adopters.
Build a Data Pipeline Dashboard to monitor ingestion and ETL.
Implement a Monitoring System:
Alerts for CPU/memory thresholds.
Checks for the latest data ingested.
Expand Dashboard APIs (in coordination with the tech team).
Improve Agent performance and reliability.
Refactor Agent execution logic by user (simplify if necessary).
Create staging environments for:
Agent
Replicats API
Data pipeline
Enable dynamic Agent configuration through LLM (RAG-based).
Allow users to schedule future configuration changes via LLM.
Add relevant RAG modules to support parameter customization and scheduling.
Start CoinGecko data ingestion.
Build an ETL pipeline to fill in missing or incorrect data.
Conduct Hurst exponent analysis (market regime shift detection).
Integrate Acolyte mindshare data for trading signals.
Define the liquid index using Dune data.
Use CME volatility surface (PDF-based) for long signals.
Add Granger causality to feature selection and calibration pipeline.
Document models, architecture, and processes.
Continue internal knowledge transfer:
Code reviews
Foundations of Agent models and implementation
Implement a staking/gating mechanism for access control.
Add support for time-limited and freemium access models.
Improving API’s performance
Data layer restructure for the application
System upgrade for Multiple Agent Deployment
Replicats is a new paradigm in automated portfolio management, combining sophisticated AI with the accessibility needed for widespread adoption.
To start using Replicat-One, visit replicats.ai and sign up for our launch.
Website: www.Replicats.ai
Documents: https://docs.replicats.ai/
Discord: https://discord.com/invite/replicatsai
Telegram Announcements: https://t.me/replicatsai
Paragraph: https://paragraph.xyz/@replicatsai
Disclaimer:
Please note that Replicat-One and Replicats are currently in the developmental stage. Features are being deployed experimentally to encourage community engagement and gather valuable feedback from our users. We want to emphasize that several platform aspects, including technical features, the business model, terms and conditions, and other relevant items, are subject to updates and additions. These updates will occur over the coming days and weeks as we work to refine and enhance the platform.