The strongest signal isn't “we need AI.”
It's that people are spending too much time on a recurring workflow that includes repetitive information work. This engagement is a good fit when teams repeatedly need to:
- Read, summarize, classify, or extract information from documents or messages.
- Research cases, accounts, customers, vendors, or internal knowledge.
- Compare information across multiple sources before making a decision.
- Draft reports, responses, recommendations, or other repeatable outputs.
- Move information between systems or coordinate multi-step processes manually.
- Review large volumes of similar cases where people still need to approve exceptions.
- Reconcile data or identify missing, inconsistent, or unusual information.
- Handle intake, triage, routing, or support workflows with repeated decision patterns.
If the workflow consumes meaningful labor, happens frequently enough to matter, and has a clear business owner, it may be worth testing. Not every manual process is a good candidate — part of the engagement is finding out which one is.
The AI Workflow Automation Assessment & Pilot
A focused, 2-3 week engagement designed to answer three questions. It begins with understanding the workflow — not selecting a model.
Where can AI actually help?
We separate steps that are suitable for deterministic automation, AI assistance, agentic orchestration, conventional software, or continued human judgment.
Can it handle this workflow reliably enough to matter?
We build and evaluate a working pilot against realistic inputs and the current process rather than relying on a slide deck or generic demonstration.
What would production implementation require?
You receive a practical architecture and roadmap covering integration, human controls, security considerations, evaluation, deployment, and the next implementation phase.
- Current process steps, handoffs, and decision points
- Volume, frequency, cycle time, and labor involved
- Documents, messages, records, and other inputs
- Systems, APIs, databases, and tools used today
- Repetitive work versus judgment-heavy work
- Error, exception, escalation, and rework patterns
- Privacy, security, and data-handling constraints
- Human approval and accountability requirements
- Existing process metrics or a practical baseline
- What a successful outcome would need to improve
We normally combine process-owner interviews with observation or walkthroughs of the actual workflow and representative sample inputs.
Understand the workflow
Kickoff, process-owner interviews, workflow walkthrough, representative inputs, systems and data review, constraints, and business baseline.
Design and build the pilot
Identify the best automation points, design the architecture and controls, implement a focused pilot, and test it against realistic examples.
Evaluate and decide what's next
Review results, limitations, production requirements, expected value, risks, and the recommended next step.
At the end of the engagement, you have a working pilot and a production decision. You are not required to hire FADLtech for implementation.
A working pilot and a production roadmap
Six concrete deliverables. The two highlighted below are the core outcome of the engagement.
Current Workflow Assessment
A concise view of how the process works today, where time is spent, which systems and data are involved, and where the largest bottlenecks or automation opportunities exist.
Automation Opportunity & Risk Analysis
A step-by-step recommendation for what should use conventional automation, AI assistance, agentic workflows, human judgment, or no automation at all — including the important tradeoffs and risks.
Proposed Solution Architecture
A practical design covering workflow orchestration, model/service choices where relevant, integrations, data flow, guardrails, human-review points, and production considerations.
Working Pilot
A focused implementation that demonstrates the highest-value part of the proposed workflow using representative inputs where practical.
Pilot Evaluation
A decision-oriented review of what worked, what did not, reliability limitations, observed workflow impact, and whether the opportunity appears worth pursuing.
Production Roadmap & Executive Readout
A recommended path to production, major dependencies and risks, rough implementation scope, and a working session with technical and business stakeholders.
The pilot should prove something useful
A pilot is not successful because an AI model produced an impressive answer once. Where practical, we compare the pilot with the current workflow using measures such as:
- Processing or review time
- Percentage of cases requiring human intervention
- Extraction or classification quality
- Research time saved
- Manual system interactions eliminated
- Error or rework reduction
- Throughput or cycle-time improvement
The exact evaluation depends on the workflow. The goal is enough evidence to support a business decision, not an artificial benchmark exercise.
What this engagement does not include
To keep the base engagement focused and fixed-fee, it does not include the following. A limited integration may be included when it is necessary to validate the pilot and is reasonably accessible within the agreed scope.
- Production deployment or organization-wide rollout
- Automation of multiple unrelated workflows
- Replacement of major enterprise systems
- Extensive custom UI or product development
- Custom foundation-model training or large-scale fine-tuning
- Comprehensive data cleanup or migration
- Formal security/compliance certification
- Production SLAs or 24/7 support
- High-volume production scaling
- Major third-party integrations requiring substantial custom engineering unless specifically scoped
A real pilot, not a preselected demo
A typical pilot works best when the customer can provide access to the people who do the work and representative examples of it. If sensitive data is involved, determining what can safely be used in the pilot may be part of the initial design work.
- A clear business owner for the workflow
- Access to 2-4 people who perform or manage the work
- Representative sample inputs, documents, messages, or records
- Existing SOPs or process documentation where available
- Information about the systems, APIs, and tools involved
- Approximate workflow volume and labor/cycle-time baseline where available
- Agreement on what a useful pilot outcome should demonstrate
- An appropriate approach for handling sensitive or regulated data
A clear, fixed-fee commercial structure
The standard engagement focuses on one workflow and is normally completed over approximately 2-3 weeks.
A relatively contained workflow with accessible systems and representative inputs may fit the standard scope. Workflows involving multiple systems, sensitive data, substantial integration work, or difficult evaluation requirements may require a larger pilot. The final fixed fee is confirmed after a short scoping conversation.
Included: workflow assessment, architecture, focused pilot implementation, evaluation, production roadmap, and executive readout.
A successful outcome isn't always “build a large AI system”
The right next step depends on what the evidence shows.
The pilot is useful even when the answer is “not yet” or “not this workflow.” You are not required to hire FADLtech for implementation.
Want the one-page overview?
Download the AI Workflow Automation Assessment & Pilot overview for a concise summary of the engagement, deliverables, timeline, and investment.
Questions buyers usually ask
Do we need to know exactly where AI should be used before we start?
No. Determining where AI belongs — and where it does not — is part of the engagement. Start with the business workflow and the problem, not a preselected model or agent architecture.
Does the pilot require production data?
Not necessarily. Representative sample inputs are often sufficient. If sensitive data is involved, determining what can safely be used in the pilot may be part of the initial design work.
Does FADLtech build autonomous AI agents?
When a bounded agentic workflow is the right tool, yes. But autonomy is not the objective. Many useful systems combine AI with deterministic software, existing APIs, and human review.
Is the pilot production-ready?
Not by default. The pilot is designed to validate the workflow, architecture, and important assumptions quickly. Production hardening, security controls, observability, scaling, and broader rollout are scoped separately where needed.
What happens if the pilot does not work?
That is a valid outcome. The purpose of the pilot is to support a sound investment decision, not to justify AI regardless of the evidence. The pilot is useful even when the answer is “not yet” or “not this workflow.”
Can FADLtech implement the production solution?
Yes. If the pilot supports moving forward and FADLtech is a good fit, production implementation can be scoped as a separate phase. You can also use the architecture and roadmap with an internal team or another provider.
What about sensitive or regulated data?
We address data-handling constraints during design. The pilot scope and technology choices must match the organization's privacy, security, and compliance requirements. This engagement is not a formal security or compliance audit.
Have a workflow that consumes too much manual effort?
Let's determine whether AI, conventional automation, or a combination can materially improve it.
No sales team. No obligation to continue into implementation. Just a practical conversation about the workflow and whether it is worth testing.