Connected workflow
Software that carries one defined task across the tools your team already uses, instead of staff moving it by hand.
Agents and workflow automation
We automate recurring tasks such as sorting requests, collecting records, and preparing updates. Rules control what can change and when a person must review it.
ScopePrototype through production release
Delivery timingDays for a focused prototype, weeks for a well-defined release when access and decisions are ready
How we check itWe test that the workflow does what it should, refuses what it should not, and recovers safely if a step fails partway.
Connect recurring tasks across applications
Recurring tasks that span several applications take staff time and invite copying errors. We map each task from start to finish, then use rules for predictable steps, models for interpretation, and a person’s approval before high-impact changes.
Good fit
- Operations teams moving work between several systems
- Back-office teams whose handoffs need judgment, not just data entry
- Software products that need multi-step research or actions
- Teams whose current automation breaks on everyday exceptions
Not the right fit
- Letting software take irreversible actions without limits or approval
- Processes no one can yet describe step by step
- Replacing a working rule-based integration just to add AI
What you get
Action controls
Limits on what the automation can change: permissions, approval steps, safe retries, and checks that stop an action from running twice.
Exception handling
A review queue for tasks that need a person, with a record of what already happened and steps to recover.
How it works
Map actions and exceptions
We map what starts the task, what counts as finished, and what can go wrong along the way.
Separate rules from AI
We handle known rules with ordinary code and use a model only for steps that need interpretation, such as reading a request.
Run controlled trials
We test normal cases, requests the workflow should refuse, interruptions, and recovery before widening its access.
Scope, cost, and ownership
What we need from you
- Approved access to each connected tool
- A staff member who can set limits on actions and review exceptions
What affects cost
- Number and reliability of integrations
- Risk of each action and the approvals it needs
- Process variation, volume, and how hard failures are to recover from
Technical scope
- Tool calling for approved actions
- Workflow state that survives restarts
- Approval steps
- Duplicate-safe retries (idempotency)
- Task-level evaluation
- Narrowly scoped permissions
- Exception recovery
Support and maintenance
Someone on your team reviews unresolved tasks. We agree who can change permissions and who investigates a failed or partially completed run.
Common questions
What happens when an update fails?
The workflow records which steps completed and sends unresolved items for review. Before retrying an update, it checks the destination system so a lost response doesn’t create a duplicate record.
Can an agent update systems of record?
Yes, with narrowly scoped tools, explicit permissions, validation checks, and approval rules matched to the risk.
When is ordinary automation better than an AI agent?
When the inputs, rules, and order of steps are known. Fixed code is easier to test in that case. A model can still handle one step, such as reading a request, while code runs the rest. An is worth considering when the request itself changes which tools or steps are needed.