Blog
AI Agents for Transaction Monitoring in Cross-Border Payments: A 2026 Guide
Why transaction monitoring queues at cross-border payment companies grow faster than the teams that work them, what an alert investigation actually involves, why regulators forbid the obvious shortcuts, and how AI agents add review capacity inside the systems you already run.
Read articleThe trust gap: why 95% of fund managers use AI and only 7% run agents
95% of fund managers use AI. 7% run agents. A former ops operator on what the gap is made of, what closes it, and what agents still cannot do.
Why Zero Trust is the Baseline for Implementing Agentic Systems
My field notes on why Zero Trust is important to building trust in agentic systems, and what we could build on top of it.
Zomma-ing towards SPIFFE: a Secure Production Identity Framework for Everyone (and their Agents)
Why Zomma assigns SPIFFE IDs to our ephemeral runtime instances the orchestrator spins up — short-lived X.509 certificates from our own trust domain make every agentic action attributable and accountable.
Can an AI agent replace data entry?
An agent handles the rule-based part of data entry, reading from one system and typing into another, faster and without the errors that creep in by hour three. The judgment calls still need a person.
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How to Automate Fund Admin and Transfer Agent Portal Work
Fund admin portals, prime broker sites, and transfer agents rarely have APIs. How hedge fund and family office ops teams automate the daily downloads, re-keying, and month-end reconciliation with computer-use agents.
Implementing the Agentic Trust Framework (ATF): Zomma's Playbook
Zomma's playbook for implementing the Agentic Trust Framework: four concern bands, deterministic controls, human approval, and an examiner-ready audit trail.
Headless vs Headful: Why Computer Use Survives an Agent-Run Internet
Headless vs headful, explained, and why an agent-dominated future still needs computer use. Most software has no API and never will, so an agent that can operate a screen can work where API-only agents can't.
Enterprise Computer Use: What It Is, How It Works, and How to Deploy It Safely
Enterprise computer use is AI agents operating software the way a person does, for regulated work that lives behind portals with no API. How it works, how it differs from RPA and APIs, and why in regulated finance the screen is the control surface, not a fallback.
Computer-Use Agents vs RPA: Why a Decade of Enterprise Automation Kept Breaking
Why RPA bots keep breaking, how computer-use agents handle a screen that changes, where each one actually fits, and why financial back offices feel the shift first.
AI Agents for KYC & Customer-Profile Review: A 2026 Guide for Compliance Teams
What a KYC customer-profile review requires, how often you actually have to do one (it's risk-based, not fixed-cadence), the rules by business type in 2026, and how AI agents clear the review backlog by working inside the compliance systems you already use.
Why your best operations person is your biggest risk
Small operations teams run on unwritten judgment. When the person who knows the exceptions leaves, the firm loses more than capacity.
How to reduce manual data entry in operations
Operations teams move data between portals, spreadsheets, CRMs, and internal systems all day. Here is how to cut that work without a large integration project.
What does it cost to automate an operations workflow?
RPA, offshore teams, internal engineering, and computer-use agents all have different economics. The right answer depends on workflow volume, risk, and maintenance burden.
Automation tools for the legacy systems teams still use
Many operations workflows still depend on old portals, desktop apps, and brittle exports. Here are the automation approaches that still work.
How long should an operations automation project take?
Traditional RPA can take months. Computer-use agents can prove value in weeks because they start where the work already happens.
How to automate computer work without an API
Most automation tools need an API. Many portals and internal systems do not have one. Screen-based agents solve a different problem.
RPA vs AI agent: what operations teams should know
RPA follows scripts. Computer-use agents read screens and adapt. Here is what that difference means for real workflows.