R
RetisIntelligent Systems

Financial intelligence network

Financial intelligence, connected by agents and owned by people.

Retis.ai builds the infrastructure around Attas: a multi-agent financial intelligence network where professionals can contribute knowledge, data, and reporting services without giving up control.

Explore productsContact usGitHub repo

Apache-2.0 licensed. The public repo includes the open-source Prompits, Phemacast, and Attas code; the Attas beta runs the newer network experience used for controlled collaboration.

AnnouncementAttas beta now presents the live network model.

The Attas page now presents the live network model: analyst personas, data APIs, report generators, renderers, and controlled contribution.

View the Attas network01Prompits

FastAPI runtimes, Plaza discovery, and verified remote practices.

02Attas

Persona agents, data APIs, report generators, and renderers for financial intelligence workflows.

03Phemacast

Phemas, pulse binding, and programmable multi-format rendering.

The Portfolio

A product family centered on controlled financial collaboration.

Prompits provides the agent runtime, Attas turns that runtime into a financial intelligence network, and Phemacast renders structured knowledge into audience-ready outputs.

Prompits

HTTP-native infrastructure for building networked multi-agent systems.

A Python runtime layer for FastAPI-based agents, Plaza discovery, pool-backed state, and verified remote practice execution.

Prompits
  • FastAPI agent runtimes with practices, user-agent surfaces, and local-first execution
  • Plaza-backed identity, discovery, relay, and verified remote `UsePractice(...)` calls
  • FileSystem, SQLite, and Supabase pools for state, credentials, and self-hosted deployments
Explore Prompits
Attas

A multi-agent financial intelligence network for controlled collaboration.

Attas connects analyst Personas, data APIs, report generators, renderers, and newsletter agents into financial workflows where each participant keeps control of their contribution.

Attas
  • Analyst-owned Persona agents that share approved judgment while keeping prompts, models, style, and private research under owner control
  • Data and filing agents that feed market prices, transcripts, exhibits, and research context into controlled workflows
  • Report, media, and newsletter agents that turn selected insight into reusable briefings, presentations, documents, and scheduled delivery
See Attas
Phemacast

A programmable pipeline for Phemas, pulse bindings, and viewer-aware rendering.

Phemacast binds structured source material to live pulse data and renders it through Phemar and Castr stages for different viewers.

Phemacast
  • Phema-centric authoring with reusable bindings, personas, and context
  • Pulse-bound execution for dynamic data injection and structured transformation
  • Composable Phemar and Castr stages for multi-format delivery
Discover Phemacast

Highlighted Service

Retis Persona turns expertise into controlled agent services.

Build a local-first Persona from approved source material, keep raw content on the owner's machine, and connect the finished expertise interface to Attas or another Retis network through Plaza and pulses.

Start Persona ServicesExplore Retis Persona
SkillPrint

Distill an expert's repeatable method, judgment rules, caveats, and output formats.

Stylecast

Calibrate writing, video/script style, tone, vocabulary, and disclosure rules.

AgentFront

Create a service entry point for Q&A, intake, summaries, reports, routing, and handoff.

MindVault

Add governed private memory, feedback loops, audit history, and versioned improvement.

Retis Persona capability map showing Persona services, owner control, and network connection

Why Retis

Built for ownership, permissions, and professional judgment.

Agent networks where contributors decide what they expose and what stays private.

Financial workflows that keep the objective, data, expert context, and final report connected.

Open, inspectable infrastructure that can be self-hosted or extended by teams with stricter controls.

Blog

Follow the thinking behind Retis on Agentic Futures.

Essays on agents, MCP, financial infrastructure, and the practical future of autonomous systems.

October 6, 2026 · 5 min read

Financial Data Needs More Than a Tool Catalog

Why discovery, comparison, and specialist agents matter — and what that looks like in practice. Connecting AI to financial data is becoming easier. Choosing suitable data still...

Read on Medium

October 5, 2026 · 4 min read

Your Data, Your Workflow: Rethinking the Financial Terminal

A flexible workspace for financial professionals to combine trusted data sources, organize research, and build reusable views with live data. Financial research rarely begins and...

Read on Medium

September 29, 2026 · 3 min read

From Data to Apps: Adding an App Builder to the Attas Agent Network

The App Consultant recommends, the App Producer creates, and Phema brings the application to your Terminal. Explore Attas . In our previous article , we explored how the Data...

Read on Medium

September 24, 2026 · 4 min read

Find, Compare, and Choose: How the Attas Data Consultant Helps You Select Data Sources

Describe what you need, compare providers, and inspect the evidence before choosing. Explore the Attas beta You know what you want to analyze. Finding the right data is another job...

Read on Medium

September 22, 2026 · 4 min read

From Data Discovery to Your Desktop: How Attas Agents Work Together

A shared registry, ranked API recommendations, and a local terminal put data selection in the user’s hands. Finding data involves more than choosing an API. You need to know what...

Read on Medium

September 18, 2026 · 3 min read

How App Consultants and the Data Browser Work Together in Attas

From application design to live data and saved snapshots. Explore Attas: attas-b.retis.ai A useful data application brings together a clear layout, connected information, and...

Read on Medium