DGi

The AI data agent for developers.

[Carlos Mendez @charlesmendez]

Ok, I am shaking a bit. I think this feels different.

For the past few weeks I’ve been experimenting combining three ideas:

1. @bchesky saying chat interfaces are not good enough
2. @karpathy’s Wiki LLM
3. @trq212 saying HTML is the new .md

The result is starting to feel like a new interface layer for agentic systems.

Not chat.

A workspace that builds itself as you use it in pure HTML.

It learns from you, adapts to the task, and visualizes what you need in real time.

I built this as another interaction layer in Groovy apart from WhatsApp, Telegram and the chat interface.

Check it out and see how it evolves. Feels different. Magical.

I want people to try it so I am giving away https://t.co/F3q6n4X3Il for free for the first 50 users. Sign up and dm me your email.

Also, this version will be up in the open source repo in 30 days https://t.co/lqVF0Zn2Hj

[Carlos Mendez @charlesmendez]

https://t.co/xVP0OoYVKe

[Carlos Mendez @charlesmendez]

We need a new class of CRM that turns conversations into context.

A system that stores not only a person’s profile, but also their relationships and how those relationships formed.

Today I am launching persona360, an open source CLI based project that moves away from field based records and focuses on conversations.

Every interaction becomes a source of structured knowledge. Conversations are captured and translated into connections, context, and evolving information.

For example:
• Who introduced this person?
• How did I meet them?
• How did they arrive at my site?

If AI systems understand these relationships, they gain deeper context. That is how humans understand networks.

Persona360 is built around that idea.
• It turns real interactions into structured relationship intelligence.
• It updates contact and company context from conversations, not manual data entry.
• It helps manage who knows who, what matters, and what should happen next.
• It stores your network the way it actually works: connected, dynamic, and contextual.

https://t.co/4FprChnBqY

[Carlos Mendez @charlesmendez]

I just couldn't take this happening to people anymore!

Today we are launching the most advanced memory layer as an OpenClaw plugin: https://t.co/huGby6j8yf

It combines several innovations to give your ClawBot true universal memory by mimicking how the human brain behaves:
- Short-term memory that uses compaction
- Mid-term memory that uses beacons
- Long-term memory that uses embeddings
- A weighted system for memory conflicts

It is free for now thanks to our friends at @modal.

[Carlos Mendez @charlesmendez]

Everyone's talking about OpenClaw's security disaster, 135,000+ instances exposed on the open internet, API keys leaking, remote code execution on anyone's machine.

So the obvious question: does https://t.co/F3q6n4X3Il have the same problems?

I audited our own codebase against every OpenClaw vulnerability. Here's what I found.
🧵

[Carlos Mendez @charlesmendez]

We’ve been working on an AI that actually does things. Basically the @openclaw alternative, but easier to install, way more powerful, and built for teams.

Features:
- Invite your team
- Integrates with data sources like Salesforce, Supabase, Meta, and many more
- Computer browser
- Creates and reads files
- Create different chats with different LLM providers
- Obsidian integration
- Code with Claude in a much nicer UI

[Carlos Mendez @charlesmendez]

If you now understand how a company like @FactoryAI can create the best coding agent, you can understand how @trydgi created the best data analysis agent.

[Carlos Mendez @charlesmendez]

Still a week to go and user growth looks good! @trydgi and experience the best data agent ever!

[Carlos Mendez @charlesmendez]

New benchmark focused on AI data agents is out, including Julius AI.

Key findings:
- @trydgi leads with an overall score of 0.9037, about 33% higher than the best generic model.

- Almost all platforms or LLMs failed on the unstructured, tougher sessions JSON. DGi asks a clarifying question, then delivers the most accurate result.

- Replit (0.6820) narrowly edges Grok (0.6661) for third.
v0 stays as the baseline at 0.0336.

- Julius shows up as a serious player in the AI data analysis space.

Report in the comments.

[Carlos Mendez @charlesmendez]

If you are looking for a reliable and accurate data agent to embed on your platform look no further @trydgi

Have your clients ask about their spend, their performance, their orders, among many more.

[DGi @trydgi]

@Dotnetster @charlesmendez @grok Free for up to 10 questions. Then $20 per month plus thinking credits which are $0.2 per minute.

[DGi @trydgi]

We are getting more than expected usage and our platform was down almost all morning. The issue has been resolved.

[Carlos Mendez @charlesmendez]

Excited to announce the DGi Developer API.
We recently shared that @trydgi is the most accurate data analyst in the market, and just this week we launched computer use.

Now you can embed our agents into your organization however you want.

[Carlos Mendez @charlesmendez]

This is the most insane demo I’ve done!

Personalization in marketing is hard to do at scale. Imagine creating an ad for every person with the right image and message based on that user’s behavior.

Traditionally, companies don’t have the bandwidth to do this, so ad agencies create a few ads for clusters of people. That makes the scope manageable.

But what if we could do hyper-personalization in minutes with @trydgi and @NanoBanana?

In this demo, we’ll upload a database of users with their purchase behavior. For each user, we’ll group their last three purchases to identify a pattern, then tell Nanobanana to create an ad tailored to that user.

This approach could scale easily, and eventually, DGi could send each ad to a database for the company to email users every day.

Check out the demo.

[Carlos Mendez @charlesmendez]

After weeks of focusing on making DGi the most accurate and reliable AI data analyst, we’ve been working on our next feature…

One of the biggest use cases we’ve seen from our users is: “go to X page, collect the data, and process it to give me the results"

Today we’re announcing Computer Operator at @trydgi . Just say “go to X page…” and it will launch a browser and perform the task.

Full demo featuring the @TheLongInvest below, where we go through an end-to-end example:

- Go to X and check The Long Investor’s stock recommendations
- Connect to my @supabase database and fetch the stocks he recommends
- Run a simple moving average on those stocks
- Give me a final recommendation on what to invest in

[Carlos Mendez @charlesmendez]

What would you prefer in a data agent:

[Carlos Mendez @charlesmendez]

New benchmark is out.

It focuses only on Data Science capabilities.

It also includes @grok, which is clearly making progress. Congrats to the team.

@trydgi continues to lead!

[Carlos Mendez @charlesmendez]

New benchmark is out.

It focuses only on Data Science capabilities.

It also includes @grok, which is clearly making progress. Congrats to the team.

@trydgi continues to lead!

cc @elonmusk

[Carlos Mendez @charlesmendez]

Today I’m sharing a full demo of @trydgi, the most reliable data agent on the market. In our benchmarks, DGi hallucinates 28% less than other AI agents.
See the full report in my recent posts.

We’re also launching data visualization in next.js apps with beautiful components.

[Carlos Mendez @charlesmendez]

One shotted dashboard by @trydgi
next.js just makes a big difference!