Product definition
A Workflow Agent is not a chatbot or a disconnected tool. It is the action layer of LUMATARRA's AI + Analytics product, focused on one repeated job with human-controlled rules.
AI + Analytics / Workflow Agents
Turn trusted signals into action, one business job at a time.
Workflow Agents are the action layer of LUMATARRA's unified AI + Analytics product: one agent, one repeated job, one measurable outcome. We build and operate them with governed data, approvals, logs, evals, source evidence, and human handoff rules so operators can trust the work.
What it does
It watches the right inputs, classifies the work, prepares or routes the next action, asks for approval where needed, logs evidence, and hands off exceptions.
What buyers get
Less dropped follow-up, faster coordination, clearer ownership, less manual drag, and proof that the agent is doing the job correctly.
How it starts
Begin with one focused workflow inside the unified product. Once it proves value, extend the same governed data, analytics, and control model to additional jobs.
Quality standard
Every agent needs example cases, evals, approval gates, source evidence, logs, failure paths, and a named business owner.
Focused action layer
Not a platform pitch. Not a bot. One governed path from signal to completed work.
The buying conversation stays simple: pick the workflow, define the result, connect the trusted data and analytics, install the agent, and prove the work. Every Workflow Agent extends the same unified AI + Analytics operating product.
Agent
One role
A specific operating role with known inputs, outputs, rules, and limits.
Job
One workflow
A repeated job the business already understands and pays humans to manage.
Outcome
One result
A measurable improvement: fewer misses, faster follow-up, better routing, cleaner visibility.
Control
Human approval
Sensitive actions stay governed by approvals, logs, evidence, and escalation paths.
Workflow examples
Start with the Workflow Agent your team can feel immediately.
Each workflow is scoped around one job and connected to the data, metrics, controls, and owners it needs. The first implementation stays small enough to prove value quickly without creating another isolated AI tool.
AI Executive Assistant for Business
Turns meetings, email, Teams messages, and loose commitments into executive briefs, owned follow-ups, decisions, blockers, and approval-ready next actions.
AI Operations Agent
Keeps project asks, client blockers, overdue items, task ownership, and operating next steps visible so delivery teams do not lose momentum between systems.
AI Finance Assistant
Monitors AR, AP, cash movement, forecast assumptions, and finance-scorecard signals for operator review and monthly close support.
AI Controller Support Agent
Prepares evidence, reminders, variance packs, reconciliation follow-through, and finance-status briefs without replacing accounting judgment.
AI Technical Writer
Drafts SOPs, release notes, help docs, implementation notes, training materials, and proposal support from source evidence and expert review.
Hosted Agent Operations
Gives each agent a governed runtime with monitoring, approvals, logs, escalation, source evidence, and Microsoft 365 or Teams handoffs.
Installation path
A simple build process that keeps trust ahead of automation.
01
Pick one job
Choose one repeated workflow with money, time, risk, or customer trust attached. No broad automation wish lists.
02
Shadow the human
Watch how the work is actually done. Capture inputs, decisions, exceptions, approvals, and what done means.
03
Build the eval set
Create 50 example cases with expected classifications, outputs, approvals, failure cases, and escalation rules.
04
Install the agent
Connect only the needed systems, build the agent, add logs, approvals, source evidence, and owner handoffs.
05
Prove the work
Measure before and after: time saved, misses caught, follow-up speed, quality, exceptions, and human approval load.
Workflow fit checklist
The right first agent has a real job, not vague AI ambition.
If the work does not repeat, does not matter, or cannot be evaluated, it is not the first Workflow Agent to build. Score one candidate workflow with the practical readiness assessment before selecting the build.
- The job repeats at least weekly.
- A human owns it today.
- Missing it costs money, time, trust, or executive focus.
- Inputs are available in systems such as email, Teams, CRM, finance, tickets, documents, or meeting notes.
- A clear done state exists.
- Human approval rules can be written down.
- At least 50 real or representative examples can be collected.
FAQ
Questions buyers ask before trusting an agent with work.
What is a hosted AI agent?
A hosted AI agent is an AI workflow product LUMATARRA operates for one repeatable business job. It runs with approval gates, logs, source evidence, monitoring, and human escalation instead of leaving teams to manage another tool alone.
What is a Workflow Agent?
A Workflow Agent is a focused capability inside the LUMATARRA AI + Analytics product. It completes one repeated business job with a measurable outcome using defined inputs, approval gates, logs, evidence, and human handoff rules.
How does this connect to LumaSphere or Executive Intelligence?
Workflow Agents turn trusted analytics into action. LumaSentials provides the governed data foundation, LumaSights provides visibility, and LumaSphere / Executive Intelligence connects the signals, decisions, agents, and follow-through.
Where should we start?
Start with one job that repeats often, costs money when missed, and has a clear definition of done: meeting follow-up, client coordination, finance visibility, support triage, sales follow-up, or document intake.
Do Workflow Agents send messages or take action automatically?
Only where the rules allow it. LUMATARRA designs approval gates, escalation paths, logs, and source evidence so sensitive actions stay controlled.
What makes a Workflow Agent ready for sale or production?
A clear job, 50 example cases, pass/fail evaluation rules, known failure modes, human approval rules, audit logs, owner handoffs, and a measurable business result.
Next step
Pick the one workflow your team should not have to chase manually.
We will map the job, define the agent, build the eval set, and show exactly what has to be approved before anything acts. Start with one agent in 30 days.