Runtime vs Rogo
Runtime is the agent harness for payment and fintech operations teams. Rogo is an AI research platform for bankers and investors. Compare users, data, actions, and deployment.
TL;DR: Runtime is the stronger choice for operations: agents that work payment, risk, and compliance queues inside your cloud and take actions with approvals. Rogo is a leading research platform for investment banks and investors.
| Feature |  Runtime |  Rogo |
|---|---|---|
| What it is | Agent harness for payment and risk ops | AI research platform for finance |
| Users | Payment ops, risk, compliance, support, finance | Bankers, investors, analysts |
| Premium market data | Connect your own sources | Built-in partnerships (LSEG, FactSet, S&P) |
| Works your internal systems | Ledger, processor, bank files, tickets | Research data and documents |
| Takes actions with approvals | Yes: replies, reserves, releases | Produces research outputs |
| Runs in your cloud | Yes, or fully self-hosted | Hosted platform |
| Each agent gets its own computer | Yes | No |
Rogo is the better fit for bankers, investors, and analysts who need AI research backed by premium market data. Runtime is the better fit for payment and fintech operations teams whose agents work queues across the ledger, processor, and bank data and take actions with approvals. Runtime is the AI agent harness for payment and fintech teams.
Rogo and Runtime at a glance
Rogo is an AI platform for global finance. Bankers and investors at firms like Rothschild, Jefferies, and Lazard use it for research: company profiles, comps, CIMs, pitch material, and diligence, backed by data partnerships with LSEG, FactSet, S&P Global, and PitchBook.
Runtime is an agent harness for payment and fintech operations. From payment ops to risk, compliance, and support, anyone on the team can build agents that work their queues on their own computers inside your cloud, called from Slack, Teams, email, SMS, or voice, with approvals and a full audit trail.
Rogo is for the front office: bankers and investors producing analysis. Runtime is for the back office: the teams that keep money moving.
How they differ
Research outputs versus operational actions
Rogo's output is research: a profile, a comp set, a memo, a deck. Runtime agents work queues and take actions, such as replying to a merchant, applying a reserve, or releasing a payout, each one approved by a person first. The output is a resolved case with the evidence attached.
Market data versus your internal systems
Rogo's strength is premium market data through its partnerships. Runtime agents work in your own systems: the ledger, the processor, bank files, and tickets, plus portals with no API through a browser on the agent's own computer.
One research team or every back-office team
Rogo serves the people producing analysis. Runtime serves every operational team that works a case, on one harness and one memory.
Data and models in your cloud
Runtime agent computers run in your AWS, GCP, or Azure account, or fully self-hosted, with any model you choose, and every run is recorded for your auditor or sponsor bank.
Where Rogo is stronger
- Premium market data. Built-in partnerships with LSEG, FactSet, S&P Global, and PitchBook.
- Banker and investor workflows. Profiles, comps, CIMs, pitch material, and diligence.
- Front-office references. Used at firms like Rothschild, Jefferies, and Lazard.
- Document outputs. Built to produce memos and decks, not just answers.
Where Runtime enters the picture
Rogo answers questions about markets and companies. The back office answers a different question: what happened to this payment. When a payout gets stuck, support gets the ticket, payment ops traces it through the processor, finance sees a recon break in the month-end close, and risk or compliance may review the account. Today each team investigates it separately in different tools. On Runtime it is one investigation with one record, and the evidence is attached to the resolved case rather than to a memo.
Teams usually start with one sharp queue, such as finance's daily reconciliation breaks, then add agents for payment ops, risk, and support on the same platform.
- No single vendor to depend on. Agents run in your AWS, GCP, or Azure account or fully self-hosted, on the sandbox provider you choose with fallbacks, and on any model (Claude, GPT, Gemini, or open-weight), with routing across Claude Code, Codex, and OpenCode.
- Guardrails you set. Agents start read-only, ledger entries, reserves, and payout releases wait for approval, credentials are masked, card numbers and SSNs are stripped, RBAC controls access, and every run is recorded.
- Built for teams. Finance, payment ops, risk, compliance, and support share agents, templates, and one memory, so a recon edge case solved once is context for the next.
- An engineer, not an account executive. A forward-deployed AI engineer with a payments and post-trade background (Hulu's payments team at Disney, Finix, Modern Treasury, BlackRock) builds the first agents with your team.
Create a banking ops agent that handles RFIs, hold-harmless requests, and returns of funds from our partner bank, verifies against our ledger, and drafts replies for my approval.
bank-ops-agent
Tools picked from your prompt
Which should you choose
Choose Rogo if
- Your users are bankers, investors, or analysts doing research
- You need premium market and company data built in
- Outputs are documents: profiles, comps, memos, decks
- The work is front-office analysis, not back-office operations
Choose Runtime if
- Your users are payment ops, risk, compliance, finance, or support teams
- Agents need to work your ledger, processor, and bank data
- Agents should take actions, with approval before money moves
- Data and models have to stay in your cloud
See Runtime on your busiest queue
Bring one SOP. A forward-deployed AI engineer builds the first agent with your team, inside your cloud.
Frequently asked questions
What is Rogo used for?
Bankers and investors use Rogo for research: company profiles, comps, CIMs, pitch material, and diligence, backed by data partnerships with LSEG, FactSet, S&P Global, and PitchBook.
Is Rogo good for fintech operations teams?
Rogo is built for front-office research, not back-office operations. Payment ops, risk, compliance, and finance teams working held payouts, returns, disputes, and recon breaks are better served by an agent harness like Runtime.
What is the difference between Rogo and Runtime?
Rogo produces research outputs from market data and documents. Runtime agents work operational queues across your ledger, processor, bank files, and tickets, and take actions like replies, reserves, and releases after a person approves.
Can Runtime run in my own cloud?
Yes. Runtime agent computers run in your AWS, GCP, or Azure account, or fully self-hosted, with any model you choose, including open-weight models in your cloud.
Where does Runtime fit next to Rogo?
Rogo serves front-office research for bankers and investors. Runtime is the AI agent harness for payment and fintech teams: it serves the back office, where payment ops, finance, risk, compliance, and support work cases across the ledger, processor, and bank data in your own cloud. They do different jobs and rarely compete.
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