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Govern every AI interaction through one layer
Approved models, budgeted tokens, governed tools, actions taken as the user, and one audit trail. Built on Workato, delivered by API People.
The problem · point to point
Every AI tool wired straight to your core systems. Each risk lands on a different desk.
Four AI tools and five systems make 20 separate connections to secure, log and pay for. Add one more AI tool and you add five more unmanaged connections.
Needs: actions tied to a named user
Today: shared service accounts; tokens in desktop config files
Needs: a registry with owners
Today: no inventory of models and agents touching member data
Needs: a log of what went where
Today: member data sent to models with no record of what left
Needs: one log: who, what, outcome
Today: evidence scattered across vendor consoles, or missing
Needs: spend by team and use case
Today: per-seat and per-token bills with no attribution
Needs: one reusable pattern
Today: every new AI tool is a new integration to secure
The governed pattern · with Workato
Every AI call through one
governed layer.
Build the
controls once, not per AI tool.
Point to point
Through Workato
Model choice
Each team picks; keys live in apps
Routes decide; swap without redeploying
Spend
Separate invoices, no attribution
Token limits per key; spend by team
Credentials
Shared service accounts on desktops
Tools run as the signed-in user
MCP servers
Anyone installs anything
Approved catalogue, by user group
Audit
Scattered across vendors, or none
One log: user, tool, tokens, outcome
Data
Raw records sent to the model
Recipes trim payloads first
Change
Ad hoc edits in production
Environments and CI/CD
Workato provides
- Model, MCP, Agent and API gateways
- Workato Identity, SSO, SCIM, verified user access
- Hosted MCP runtime, 1,200+ connectors
- Activity audit log and streaming
- SOC 2 Type II, ISO 27001, PCI DSS
API People adds
- Core-banking MCP tools: Jack Henry, Fiserv, FIS
- Policy templates: routes, budgets, tool tiers
- Control-evidence pack for exams
- Workshop, POC and delivery
- Managed AI governance service
The client owns
- AI use policy and risk appetite
- Model risk review of each use case
- Desktop and network controls
- Identity provider and access reviews
- LLM vendor contracts
The gateway governs what flows through it. Blocking unsanctioned MCP servers and AI apps on desktops stays with the client's endpoint and network controls.
Justifying the layer
Four levers the CFO can audit
Skip months of custom development. Our marketplace of production-ready connectors links Jack Henry, Fiserv and leading enterprise platforms to the apps your business runs on — securely and out of the box.
LLM spend
Route routine prompts to cheaper models, cap tokens per key, trim tool payloads.
Measure: monthly spend by teamBuild avoided
No in-house model proxy, MCP hosting, token exchange or audit pipeline to staff.
Measure: FTEs and infra avoidedExam effort
One attributed log and an AI inventory replace evidence gathered by hand.
Measure: hours per exam cycleCredential risk
Shared AI service accounts are retired in favour of per-user access.
Measure: standing AI credentials retiredNet annual value = LLM spend avoided + build and run avoided + exam hours saved + risk retired − (Workato subscription + API People services)
Regulatory fit · US
Map each control
to
what examiners ask
AI and model inventoryRegistry of models, routes, tools, agents
SR 26-2: Fed, OCC, FDIC, Apr 2026; replaced SR 11-7
Vendor and LLM riskSwap model providers without redeploying
Least privilegeVerified user access, SSO, group-based tools
Monitoring and auditPer-user activity log streamed to SIEM
Change managementEnvironments, CI/CD for recipes and agents
FFIEC · model lifecycle under SR 26-2
Data minimizationRecipes return only the fields needed
GLBA privacy · state privacy laws
How we start
Prove it on your
systems
before you buy
Skip months of custom development. Our marketplace of production-ready connectors links Jack Henry, Fiserv and leading enterprise platforms to the apps your business runs on — securely and out of the box.
Step 1 · Free
Governance workshop
- Map your AI tools, MCP servers and keys
- Rank the risks by committee seat
- Pick two or three use cases
Half day
Step 2 · On us
Proof of concept
- Your AI desktop through the gateway
- Tools on your core or CRM, as the user
- Your baseline on the four value levers
2–3 weeks · agreed exit criteria
Step 3
Governed AI foundation
- Production gateways and policies
- Core-banking tool library
- Exam evidence pack, managed service
Scoped from the POC results
- faq
AI Governance, answered
What is AI governance for banks and credit unions?
AI governance routes every AI interaction through one layer: approved models, budgeted tokens, governed tools, actions taken as the user, and one audit trail. API People builds it on Workato.
Why set up AI governance before AI spreads?
Governance is cheapest before AI spreads. Controls added later mean unwinding keys, shared accounts and one-off integrations. Starting early means no AI sprawl across desktops and agents, no new technical debt to retire later, and rollback stays possible.
What does it mean for an AI agent to act as the user?
Instead of one shared service key, each employee works through their own login in Workato. The audit trail names the employee, the tool and the result, and your core systems enforce each person's rights.
Which US regulations does the AI governance layer map to?
Each control maps to what examiners ask: AI and model inventory to SR 26-2; vendor and LLM risk to the interagency third-party risk guidance (2023); least privilege to GLBA safeguards, NCUA Part 748 and NYDFS Part 500; monitoring and audit to the FFIEC IT Examination Handbook; change management to FFIEC and the model lifecycle under SR 26-2; and data minimization to GLBA privacy and state privacy laws.
What does Workato provide and what does API People add?
Workato provides the Model, MCP, Agent and API gateways, Workato Identity with SSO, SCIM and verified user access, a hosted MCP runtime with 1,200+ connectors, and an activity audit log. API People adds core-banking MCP tools for Jack Henry, Fiserv and FIS, policy templates for routes, budgets and tool tiers, a control-evidence pack for exams, and a managed AI governance service.
Does the AI gateway block unsanctioned AI apps on employee desktops?
No. The gateway governs what flows through it. Blocking unsanctioned MCP servers and AI apps on desktops stays with your endpoint and network controls.
How do we get started with AI governance?
Start with a free, half-day governance workshop to map your AI tools, MCP servers and keys, rank the risks by committee seat and pick two or three use cases. Next comes a proof of concept on us, 2–3 weeks with agreed exit criteria. The governed AI foundation is then scoped from the POC results.
Get started
Every AI request should answer three questions
Who asked, what it touched, what it cost.
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