Multi-step operations
Translate requests into tasks, effort, cost and dependencies. Coordinate agents and software, then use verified outcomes to recalibrate the next plan.
AI Operations Systems
AI operations systems coordinate work across agents, software and people. We build the workflow around the request, with defined access, tracked progress and checks before the work is closed.
Build the System Around the Work
The surrounding workflow software decides what can run, what happens next and when a person is needed. Its rules are part of the build.
State and recovery
Track completed and pending work. Define how interruptions, unavailable tools and repeated requests are handled before the system takes action.
Checks and oversight
Set approval points, resource limits and acceptance criteria. Give your team an activity record they can use to review the work.
Example Workflow
From a Request to a Checked Result
An illustrative operations loop. Its steps and approval points are designed for the work being built.
Understand
Identify the outcome, constraints and information needed.
Plan and assign
Choose tasks, approved tools and the people who need to contribute.
Execute
Carry out the plan within access and resource limits.
Verify
Check the result and return incomplete work for review.
The Harness Holds the Controls
The model interprets information. The surrounding AI harness manages state, permissions, limits and recovery. Important changes can wait for a person; the exact boundaries are agreed before implementation.
Systems and demonstrations
Explore the workflow, the controls and the decisions people retain.
Demonstration
AI Control Plane
A shared control layer runs insurance, mortgage and finance workflows through one engine. It routes tasks to model tiers, holds sensitive actions for a person and records the workflow’s decisions and results.
Receive and route
Intake identifies the workflow and routes the task to an appropriate model tier through a shared entry point.
Check and approve
Policy checks and a named human gate govern a proposed high-risk action before it can proceed.
Record and compare
The demonstration records reason codes and compares measured tokens, elapsed time and cost for the same task across model tiers.
Controls and responsibility
Policy failures are recorded too. Checks cover authority and excluded or masked information. The self-hosted comparison is labelled as a benchmark; it is not a general savings promise.
Demonstration
Financial Preparation Harness
Prior-period records and current financial statements become a structured, formula-driven review package. AI proposes document interpretations and mappings; code validates them and produces the figures for professional approval.
Map and validate
Propose the account mappings, validate them in code and build preliminary figures for the first approval gate.
Calculate and reconcile
Software computes adjustments and builds the workpaper, source references and open-item list. Items that do not tie are flagged.
Review and export
A professional approves the prepared work before spreadsheet and import-file exports. Corrections rerun the affected stages.
Controls and responsibility
Figures come from code. Approval gates retain professional authority. Outgoing model requests are checked for excluded sensitive fields, and the administration view records model-tier cost per run.
Demonstration
Marketing Operations
A cross-brand operations view connects specialist marketing agents, a lead pipeline and an outreach console. Proposed outbound messages pass a safety check and a person before sending.
Bring the activity together
A shared view organises performance across brands and channels, with personal data masked in the lead pipeline.
Run specialist checks
Agents handle content routing, campaign go-live checks, campaign variance, sponsorship review and cross-channel reconciliation.
Review outreach
Every proposed outbound message passes the safety gate and human approval.
Controls and responsibility
Outbound messages do not send themselves. The lead pipeline masks personal information and the person reviewing outreach retains the sending decision.
Questions About the Service
How is this different from an AI agent?
An agent handles a task or makes a plan. An operations system coordinates the wider workflow, including tools, state, other agents, approvals and result checks.
Can it work with our existing software?
We review the systems and access available, then scope the required connections. Compatibility and permitted actions are checked rather than assumed.
Who operates it after launch?
Operating responsibilities and support are agreed with your team. The build includes testing and handover guidance, with operational support defined for the engagement.
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Tell Us What You Want to Build
Bring a workflow, a requirement or a problem your team wants to solve.