Revomo AI · Intelligence architecture

Scale commercial decisions.
Keep control.

Connect AI models, commercial context and decision engines with governed execution. Build on an intelligence architecture that can evolve with your business.

  • Commercial understanding
  • Model flexibility
  • Governed execution
The architecture

One connected system for commercial intelligence.

Commercial context, AI models, decision engines and workflows work together under shared controls.

FIG 01 · System mapHow the architecture works

Entry points

Revomo Copilot

Solution Interfaces

Events

Schedules

APIs 

Defined workflow

Agent reasoning

Governed Execution

Identity · Permissions · Approvals · Audit

Execution

Workflow Orchestration

Defined workflows and agent steps

Agent Harness

Context · Reasoning · Tool use

Model Hub & Gateway

Model selection · Routing · BYOM

Authorized Tools & Actions

Read and update records

Execute decision models

Shared commercial foundation

Commercial Context

Shared entities, definitions and lineage

Decision Engines

Calculate, predict, simulate, optimize

Invoke agent
Return result
Model request
Response
Inputs & definitions

Entry points

Revomo Copilot

Solution Interfaces

Events

Schedules

APIs 

Defined workflow

Agent reasoning

Governed Execution

Identity · Permissions · Approvals · Audit

Execution

Workflow Orchestration

Defined workflows and agent steps

Agent Harness

Context · Reasoning · Tool use

Model Hub & Gateway

Model selection · Routing · BYOM

Authorized Tools & Actions

Read and update records

Execute decision models

Shared commercial foundation

Commercial Context

Shared entities, definitions and lineage

Decision Engines

Calculate, predict, simulate, optimize

Invoke agent
Return result
Model request
Response
Inputs & definitions

Entry points

Revomo Copilot

Solution Interfaces

Events

Schedules

APIs 

Defined workflow or agent reasoning

Governed Execution
Identity · Permissions · Approvals · Audit

Execution

Workflow Orchestration

Defined workflows and agent steps

Invoke agent · Return result

Agent Harness

Context · Reasoning · Tool use

Model request · Response

Model Hub & Gateway

Model selection · Routing · BYOM

Authorized Tools & Actions

Shared commercial foundation

Read and update records

Commercial Context

Shared entities, definitions and lineage

Inputs & definitions

Decision Engines

Calculate, predict, simulate, optimize

Execute decision models

Entry points

Revomo Copilot

Solution Interfaces

Events

Schedules

APIs 

Defined workflow or agent reasoning

Governed Execution
Identity · Permissions · Approvals · Audit

Execution

Workflow Orchestration

Defined workflows and agent steps

Invoke agent · Return result

Agent Harness

Context · Reasoning · Tool use

Model request · Response

Model Hub & Gateway

Model selection · Routing · BYOM

Authorized Tools & Actions

Shared commercial foundation

Read and update records

Commercial Context

Shared entities, definitions and lineage

Inputs & definitions

Decision Engines

Calculate, predict, simulate, optimize

Execute decision models

Shared context grounds the work. Models reason. Engines compute. Workflows coordinate. Controls govern execution.
Commercial context & decision engines

Intelligence grounded in your commercial world.

Connect AI to shared business definitions, commercial relationships and decision engines, so reasoning draws on the context and calculations that matter.

Explore Commercial Context
Model Hub, routing & AI Gateway

Evolve your models. Keep your commercial foundation.

Work with a collection of models through Revomo’s Model Hub, route requests to configured models, and bring your own model. Keep commercial context, tools and workflows connected as model choices evolve.

Model Hub
Work with a collection of supported models.
Routing
Direct requests according to supported configuration and routing policies.
BYOM
Connect a model you provide.
Explore model access and routing

Routing. Routing policies are configured in Revomo; the router applies them to each request, and a workflow or agent can be pinned to a specific model. The model interprets and drafts; commercial figures come from the decision engines.

AI Gateway. The gateway connects and mediates model access for the agent harness. Models run outside Revomo; permissions and approval policies govern commercial actions on either path.

Inference. Revomo-provided inference runs on Amazon Bedrock, a listed subprocessor in the Data Processing Addendum. A model you bring runs under your arrangement with its provider. Model support is confirmed for each configuration.

Illustrative · generic model labels

The selected model runs on Revomo-provided inference.

Agent harness & orchestration

Connect reasoning to governed execution.

The agent harness brings context, model interaction and authorized tools into an execution loop. Workflows coordinate defined steps and agent-assisted work under your policies.

Explore how agents execute

Context. The harness assembles the relevant records, rules and recent changes before the model plans.

Authorized tools. The tool list is filtered to the caller's role before the model sees it; each tool is marked read, draft or live.

Orchestration. A workflow follows its defined path and can invoke an agent step, then continue with its result. A live change is a lifecycle transition the approval policy adjudicates.

Limits. 30 steps, then the agent pauses and asks; two consecutive tool failures stop the run; abort is checked before each tool call. The loop is implemented on LangGraph.

Explore Agents & Automations
Control, observe & improve

Operate with control. Improve with evidence.

Set boundaries for AI work, inspect execution and evaluate changes. Use reviewed feedback to guide improvement.

AI usage controls

Keep AI work within defined limits.

Apply usage allowances and execution boundaries.

AI observability

Inspect every stage of execution.

Follow the steps, tool calls and outcomes behind a run.

Illustrative run · every stage is kept on the run record
Evaluations

Check changes before release.

Compare observed behavior with defined expectations.

Illustrative evaluation set · commercial-rule validation is a separate scope, in the details below
Continuous learning

Improve guidance through reviewed feedback.

Turn execution evidence into changes people approve.

Guidance changes only after approval · no automatic model retraining

Permissions and approval policies remain in force throughout execution. See security and governance

Explore controls and evaluation details

Usage and execution limits

Usage quotas
Configured quotas bound AI consumption. With your own model, model charges are billed by that provider.
Execution limits
30 steps, then the agent pauses and asks. Two consecutive tool failures stop the run with an explanation. Abort is checked before each tool call.

Run records and audit

Run records
One per execution, with every effect it produced. An agent step keeps its prompt, reply and the tools it used.
Audit
Each agent tool call is written to the audit trail with the resource it touched. Transitions are logged against the person who signed.

Evaluations

Agents
Agent evaluations check an agent's behavior on defined tasks against expected results.
Commercial rules
A separate scope: rules, formulas and price lists are validated against cases with a known outcome. Passing a rule check does not establish overall agent quality.

Continuous learning

Today
Feedback and run records are reviewed, and an approved change updates the instructions agents use in future runs, versioned like any other change. Models are not retrained automatically, and nothing is learned across customers.
Product direction
Learning from decision history through a trace-derived context graph is a concept, not shipping functionality. It is drawn below.
Product directionLearning from decision historyConcept
Agent traces

 

 

 

 

 

Copilot · tool · engine · Copilot · publish

Commercial context graph

Relationships between

decisions and outcomes

Probabilistic

decision paths

A pattern qualifies

after evaluation and review

Approved guidance for the next run

Abstracted traces

review → evaluate → draft

tool family →

Raw values and identities

are removed before patterns form

Cost pass-through

Margin recovery

Renewal pricing

Commercial context

Customers

Agreements

Prices

Products

Costs

Transactions

Reconciles identities and entities · lineage from any figure to its record

Workspace activity graphs

Clusters events into tasks and workflows

Permission boundaries

Review cost update

Evaluate levers

Draft price action

Quote request

Price guidance

Approve

Connectors & observability

ERP

CRM

Price lists

Cost files

Agreements

Quotes

Events: cost updates, price changes, quotes, orders, renewals, approvals, publishes

Reinforces paths

Flags paths

that held

that failed

Observed pattern

Evaluation

Review

Approved guidance

inside your organization

Agent traces

 

 

 

 

 

Copilot · tool · engine · Copilot · publish

Commercial context graph

Relationships between

decisions and outcomes

Probabilistic

decision paths

A pattern qualifies

after evaluation and review

Approved guidance for the next run

Abstracted traces

review → evaluate → draft

tool family →

Raw values and identities

are removed before patterns form

Cost pass-through

Margin recovery

Renewal pricing

Commercial context

Customers

Agreements

Prices

Products

Costs

Transactions

Reconciles identities and entities · lineage from any figure to its record

Workspace activity graphs

Clusters events into tasks and workflows

Permission boundaries

Review cost update

Evaluate levers

Draft price action

Quote request

Price guidance

Approve

Connectors & observability

ERP

CRM

Price lists

Cost files

Agreements

Quotes

Events: cost updates, price changes, quotes, orders, renewals, approvals, publishes

Reinforces paths

Flags paths

that held

that failed

Observed pattern

Evaluation

Review

Approved guidance

inside your organization

Agent traces

 

 

 

 

 

Copilot · tool · engine · Copilot · publish

Approved guidance shapes the next run; each run feeds back which paths held and which failed

Commercial context graph

Relationships between decisions and outcomes · probabilistic decision paths · a pattern qualifies after evaluation and review, inside your organization

Abstracted traces

review → evaluate → draft

tool family →

Cost pass-through

Margin recovery

Renewal pricing

Raw values and identities are removed before patterns form

Commercial context

Customers

Agreements

Prices

Transactions

Products

Costs

Reconciles identities and entities · lineage from any figure to its record

Workspace activity graphs

Review cost update

Draft price action

Quote request

Approve

Clusters events into tasks and workflows · permission boundaries

Connectors & observability

ERP

CRM

Price lists

Cost files

Agreements

Quotes

Events: cost updates, price changes, quotes, orders, renewals, approvals, publishes

Observed pattern

Evaluation

Review

Approved guidance

Agent traces

 

 

 

 

 

Copilot · tool · engine · Copilot · publish

Approved guidance shapes the next run; each run feeds back which paths held and which failed

Commercial context graph

Relationships between decisions and outcomes · probabilistic decision paths · a pattern qualifies after evaluation and review, inside your organization

Abstracted traces

review → evaluate → draft

tool family →

Cost pass-through

Margin recovery

Renewal pricing

Raw values and identities are removed before patterns form

Commercial context

Customers

Agreements

Prices

Transactions

Products

Costs

Reconciles identities and entities · lineage from any figure to its record

Workspace activity graphs

Review cost update

Draft price action

Quote request

Approve

Clusters events into tasks and workflows · permission boundaries

Connectors & observability

ERP

CRM

Price lists

Cost files

Agreements

Quotes

Events: cost updates, price changes, quotes, orders, renewals, approvals, publishes

Observed pattern

Evaluation

Review

Approved guidance

A concept: traces become patterns, and reviewed patterns guide the next run, inside your organization.

Explore the intelligence behind your commercial operations.

Discuss how Revomo’s architecture fits your data, model choices and governance requirements.

How your data is used

Your data supports analysis, predictions and recommendations in your workspace and is not used to train third-party foundation models. Revomo-provided inference reaches those models through Amazon Bedrock. Where you bring your own model, it runs under your arrangement with its provider. Aggregated, de-identified data may improve the service, as the Data Processing Addendum sets out.

Plate B2 · Series 2026