Keep up with latest product news

Demo link updated: https://8b79-2804-1928-216d-4301-ed37-88a5-1969-d364.ngrok-free.app/

Included a pre-built Tester Agent that can be used in the public demo. This implements idea: DPI-I-439


The Memory card: your notes and your answers
09:14 decision (mailbox): digest. OcuTalon's code builds the notes each time you look, from its own records. No model writes them, and they never hold what an email or other arriving message says: no sender, subject or text. A day stops at 2,000 characters, with "(more not shown)".This was noise, and your approval answers
Got it in the web chat and on the Simulated phone
Daily digest
Settings
ocutalon account of your own install. Visitors to the online demo aren't admins, so try this on your own install..env: the page never shows or asks for one. A provider whose key isn't set shows "No key set. Add {variable} to .env." Anthropic is the only provider listed.Fixes
Data kept
Docs and install
./install.sh, the Docker image's build and the Python packages OcuTalon installs are unchanged since 1.0.4.Requires the InterSystems IRIS for Health AI Hub Early Access image, build 154 or build 109. Upgrading from 1.0.4 keeps your conversations, reminders, watches, approval requests, settings, memories, documents and Telegram pairing. The online demo runs 1.0.5.

Frontend redesign for container and live demo. No Backend changes were added.

Shutter 1.3.2 is a patch on 1.3.0.
Full change log: https://github.com/MxSalata/shutter/blob/main/CHANGELOG.md
Knos turns any research into a product billions of people use, in days, not years. Knos carries research across the valley of death, toward Kardashev II and III. Description updated.

Initial release of Allfedo's native IRIS AI Hub food-rescue workflow.
Includes signed-in kitchen, receiving, coordinator and collector views; reviewed food invitations; shared-capacity checks; actual handoff and receipt records; changed destinations; linked returns and disposal; and local SMTP notifications.
Tested on AI Hub Community 2027.1.0AI.109.0. Fresh installation, native checks and the complete browser journey passed. Demo partners and physical events are fictional.
Source release: https://github.com/snowsadh/iris/releases/tag/v0.1.0
Validation: https://github.com/snowsadh/iris/blob/main/doc/VALIDATION.md



Shutter 1.3.0 adds pathology, tier B: when a receiver of orders and results has an outage, Shutter lists the messages that never reached it, for a person, and explains each failed order or result. Shutter still sends none of them.
Full change log: https://github.com/MxSalata/shutter/blob/main/CHANGELOG.md

Shutter 1.3.0 adds pathology, tier B: when a receiver of orders and results has an outage, Shutter lists the messages that never reached it, for a person, and explains each failed order or result. Shutter still sends none of them.
Full change log: https://github.com/MxSalata/shutter/blob/main/CHANGELOG.md

Shutter 1.2.1 fixes what the checks run on 1.2.0 found on IRIS 2026.2 and AI Hub build 154.
Full change log: https://github.com/MxSalata/shutter/blob/main/CHANGELOG.md

Shutter 1.2.0 brings everything since 1.0.1 to Open Exchange: an assistant that answers questions about the screen you're on, the tools a hospital needs before a pilot, outage watching, clearer screens, and fixes from three rounds of independent review. The safety rule hasn't moved: the AI board proposes, a deterministic gate decides, and a person or the site's written policy releases every write.
Full change log: https://github.com/MxSalata/shutter/blob/main/CHANGELOG.md

DICOM3D AI Hub is a research imaging application demonstrating native InterSystems AI Hub agents within an IRIS for Health Interoperability workflow.
%AI.Agent.Includes source code, installation instructions, research-data attribution, and documented qualification evidence.
InterSystems Community AI Hub Build 154, required FHIR images, and model weights are obtained separately and are not redistributed.
This is a research prototype, not a clinical diagnostic application.
The Safe Demo is not yet hosted and currently requires WebGPU. A WebGL fallback remains unqualified.
Native AI Hub execution has been demonstrated, but intermittent inference failures and incomplete repeatability testing remain disclosed.
Source: https://github.com/KennethJSmithDev/DICOM3D_AI


Documents
## headings, a PDF's are its pages (Page 1, Page 2 and so on) and a Word file's are its Heading 1 headings.Daily digest
Got it on Telegram
Fixes
Demo guide
Docs and install
documents tool and says how it is classified: safe and read-only, but its output is never trusted, and each search returns at most 5 passages.documents entry to the ToolClassification setting of Decide and keeps every other entry there.TurnToolsClass, and the reply filter's new form, Filter(text, hostData)../install.sh, the Docker image's build and the Python packages OcuTalon installs are unchanged since 1.0.3.Requires the InterSystems IRIS for Health AI Hub Early Access image, build 154 or build 109. Upgrading from 1.0.3 keeps your conversations, reminders, watches, approval requests, settings, memories and Telegram pairing. The online demo runs 1.0.4.





Initial release for the InterSystems "AI Agents" contest.
docker compose up; without an API key it replays the recorded Claude outputs.
This update adds a full InterSystems IRIS Interoperability production, Copilot.Interop.Production. In it, the AI agents powered by InterSystems AI Hub are regular workflow components, with queues, message trace, audit and auto-start.
Ask workflow: every question asked in the portal
Copilot Ask Service → Copilot Ask Process → AI SQL Agent ⇄ IRIS SQL Executor → Audit Log
The AI SQL Agent (business operation, %AI.Provider) turns the question into IRIS SQL, using the database catalog and the business glossary.
The IRIS SQL Executor validates the query (read-only guard) and runs it.
The self-correction loop is explicit. When IRIS returns an error or an empty result, the business process sends the real IRIS error back to the agent as a new message, up to 3 attempts. Every attempt is visible in the message trace.
Every interaction is recorded by the Audit Log operation.
Report and alert workflow: scheduled or on demand (BPL)
Report Scheduler (Ens.InboundAdapter) / Report Trigger → Report Process (BPL) → IRIS SQL Executor → alert rule → AI Report Agent → Report Publisher → Webhook Notifier → Audit Log
Users schedule any result as a report, with a frequency, optional alert thresholds and an optional webhook.
The AI Report Agent runs the autonomous %AI.Agent (with its %AI.ToolSet) to write the report narrative.
The Report Publisher writes each report to disk through EnsLib.File.OutboundAdapter and shows it in the portal. The data table always comes from IRIS, never from the LLM.
The Webhook Notifier posts alerts and reports to external systems such as Microsoft Teams, Slack or automation tools.
A sample “Daily revenue check” subscription runs at startup, so a report and its trace are available on first launch.
Visibility
Workflows page in the portal: production status, live message counts per component, scheduled reports with Run now, generated reports and a built-in message trace viewer.
Every answer shows a 🔀 session N badge that opens the trace of that question.
IRIS Management Portal: the AI Hub images ship without a web server, so a new InterSystems Web Gateway container serves the standard portal at http://localhost:52773/csp/sys/UtilHome.csp. It gives access to the production configuration, the BPL editor, the Message Viewer and the Visual Trace.
Security and privacy
User privileges preserved: production jobs run under the IRIS service account, so the catalog is built in the signed-in user’s own process and the validated SQL is executed again as that user before any data is shown.
Privacy mode (PRIVACY_MODE=1): no data value is ever sent to the LLM, only the question and metadata. Result analyses use aggregated statistics only, and none for results smaller than 10 rows, to prevent re-identification. This supports LGPD/GDPR-sensitive scenarios.
Graceful fallback: if the production is stopped, the portal keeps working through direct calls.
Validation
Rebuilt from scratch and tested end to end on iris:2027.1.0AI.108.0:
Interoperability is enabled in the namespace and the production and BPL compile without errors.
The production auto-starts.
Both workflows completed successfully, including the self-correction loop and a triggered alert.
The Management Portal Visual Trace and production configuration were checked in the browser.
Repository: https://github.com/Andre-Dienes/iris-dashboard-ai (see the “AI agents in interoperability workflows” section of the README).

Initial release: IRIS AI Hub agent proposals, independent coding checks, guided algebra practice, and Docker installation verified.Initial Release

IPM package published to the public registry: zpm "install interop-ops-agent". module.xml version 0.2.2, no code change.