Current workflow map
Inputs, people, systems, handoffs, delays, and exception paths.
AUTOMATION CONSULTING
AI automation consulting that leads to working software
Find the operational workflows worth automating before spending money building the wrong thing.
01
AI interprets.
02Software controls.
03People own consequential decisions.
WHO THIS IS FOR
When assessment is more valuable than another prototype
Consulting is appropriate when the opportunity is visible but the right automation boundary, architecture, or production path is not yet clear.
STARTING PRINCIPLE
We do not begin with the model.
The first question is not “Which AI model should we use?” It is “Which part of this process is costing the business enough time or effort to justify changing it?” Technology is selected after the process, value, constraints, and responsibility boundaries are understood.
SCOPE
A practical assessment package
The output is intended to support a build, a no-build decision, or a better-defined next step.
Automation boundary
What should run automatically, stop, or require human responsibility.
Integration map
Required systems, access, APIs, data movement, and technical dependencies.
Responsibility design
Model tasks, deterministic software tasks, validation, permissions, and review points.
Exception and production map
Failure paths, retries, monitoring, security, deployment, and operating requirements.
Implementation scope
A bounded first release, dependencies, acceptance checks, and recommended next step.
WORKFLOW
How an opportunity is evaluated
A valuable candidate is frequent enough to matter, bounded enough to control, and measurable enough to evaluate.
- 01
Observe the current process
- 02
Measure manual effort and frequency
- 03
Map systems and exceptions
- 04
Identify risk and interpretation needs
- 05
Validate technical feasibility
- 06
Scope the smallest useful implementation
If the business value, access, or control boundary does not justify implementation, the useful result may be a clear no-build decision.
RESPONSIBILITY BOUNDARIES
AI interprets. Software controls.
Models handle ambiguous inputs; human review is placed where judgment, responsibility, or uncertainty matters.
- Document and message interpretation
- Classification and extraction
- Image or video analysis
- Matching inconsistent information
- Summarization
- Permissions and validation
- Calculations and business rules
- API calls and database writes
- Workflow state and deterministic routing
- Retries, duplicate protection, and audit logs
FAILURE CONTROL
Production questions belong in the assessment
A prototype path is incomplete until failure, recovery, permissions, observability, and ownership are understood.
Technical uncertainty
Use targeted research or a bounded prototype to validate the uncertain part rather than the whole vision.
Operational exceptions
Document the cases that stop, retry, need more data, or require a person.
Production readiness
Define deployment, security, monitoring, documentation, and support requirements before estimating the build.
HOW WE WORK
Discover, scope, validate, build, operate
The engagement can stop after a useful assessment or continue into implementation and support.
Discover
Understand the work, people, systems, business value, and current evidence.
Scope
Set the automation boundary, responsibilities, exceptions, and measurable pilot goal.
Validate
Research access and APIs, test uncertain assumptions, and confirm feasibility.
Build
Implement the agreed workflow with production controls and acceptance checks.
Operate
Monitor, support, document, hand over, or improve according to the agreed model.
SCOPE AND COST
What affects assessment cost?
Scope depends on how much evidence already exists and how much technical uncertainty must be resolved.
- Number of workflows
- Number of systems
- Stakeholder complexity
- Documentation quality
- API research
- Technical uncertainty
- Deployment and security constraints
- Prototype requirements
OWNERSHIP
Ownership and handoff
Possible deliverables depend on the engagement. The ownership and deployment model is agreed before implementation begins.
CLIENT WORK
The problem was not “introduce AI.”
For the procurement workflow, too much manual work happened before someone could determine whether an opportunity was commercially attractive. The assessment focused on intake, supplier checks, calculations, risk, and the point where a person remained responsible.
See how the procurement workflow was implementedRELATED CAPABILITIES
Continue with the part of the workflow you need
FAQ
Practical questions before you start
Do we have to hire DapperAgent to build the result?
No. The assessment can support an internal team, another implementation partner, or a decision not to build. Ownership and deliverables are agreed in scope.
What if automation is not worth building?
That is a valid result. A useful assessment should identify weak value, unsuitable access, excessive risk, or a simpler process change before implementation spending.
Can you productionize an existing prototype?
Yes, after reviewing its architecture, data, evaluation evidence, permissions, failure behavior, security, deployment, and maintainability.
Can you work with our engineering team?
Yes. Responsibilities, interfaces, documentation, review, and handoff can be shaped around your internal capabilities.
NEXT STEP
Choose the workflow before choosing the technology.
Bring the candidate processes, current pain, and known systems. We will assess where automation is justified and what a responsible first implementation requires.