Task and interaction design
Define the employee, business task, inputs, outputs, instructions, source needs, success criteria, exclusions, uncertainty behavior, and handoff to a person.
AI assistant development in Savannah
Give your team an assistant designed for one real job.
F09 Tech builds task-specific AI assistants that help employees find information, prepare work, draft, summarize, compare, and use approved tools with clear permissions, review, and accountability.
- Task-specific copilots
- Approved tools
- Human approval
- Measured rollout
AI assistant map
- 01Define the user and task
- 02Limit knowledge and tools
- 03Test outputs and actions
- 04Pilot, measure, and improve
A narrow job connected to appropriate access, evidence, approval, feedback, and ownership
AI assistant services
Helpful enough to save time, bounded enough to supervise.
The value comes from the complete work design: a clear task, approved context, minimum tool access, structured outputs, human checkpoints, evaluation, logging, training, and an owner who can improve or stop the system.
Knowledge, tools, and permissions
Provide only the approved sources, functions, records, fields, and access needed for the task, with identity, scope, retention, and revocation documented.
Human review and evaluation
Add confirmations for important actions, source evidence for claims, validation rules for structured outputs, evaluation scenarios, and clear employee responsibility.
Workflow integration and operation
Connect approved systems, log meaningful activity, handle timeouts and failures, monitor usage and quality, manage cost, collect feedback, and control changes.
How the engagement works
Start with the job description, not a general-purpose agent.
We choose one valuable employee task, observe how it is completed today, define the assistant's exact role, build with minimum access, test realistic failure cases, and pilot with measurable human oversight.
- 01
Choose
Select a frequent task with a clear user, input, desired output, current effort, exceptions, accountable owner, and measurable result.
- 02
Design
Define instructions, approved sources, data handling, tool functions, permissions, validation, approval points, stop conditions, and escalation.
- 03
Build
Configure the assistant, identity, retrieval, tools, structured outputs, logs, alerts, failure handling, user interface, and administration.
- 04
Evaluate
Test common, ambiguous, incomplete, sensitive, adversarial, out-of-scope, tool-failure, and high-impact scenarios with intended users.
- 05
Pilot
Release to a controlled group, measure quality and time, review corrections and overrides, train users, and expand only when evidence supports it.
What gets delivered
An assistant employees can understand, test, and challenge.
The implementation documents the intended task, information and tool boundaries, human responsibility, test evidence, operating procedures, and conditions for expanding or stopping use.
OWASP guidance on excessive agencyOWASP identifies excessive functionality, permissions, and autonomy as core risks when language-model systems can use tools. We reduce those risks through narrow functions, minimum access, independent validation, human approval, logs, and stop conditions.- User, task, current workflow, inputs, outputs, exceptions, business value, success criteria, and exclusions
- Assistant instructions, approved knowledge, data handling, tool functions, permissions, and identity design
- Human approval, validation, source evidence, logging, alert, failure, escalation, and stop conditions
- Evaluation set and results covering quality, evidence, permissions, tools, safety, cost, latency, and usability
- Pilot plan, user training, feedback method, adoption measures, correction workflow, and acceptance decision
- Administration, access review, vendor, monitoring, cost, change, incident, and improvement ownership
Good fit signals
A strong fit when a repeatable task still needs employee judgment.
An AI assistant is most valuable when people spend meaningful time preparing or finding information, the business can define an acceptable result, and a responsible employee remains available to review the work.
- Employees repeatedly research the same approved sources before drafting, summarizing, comparing, or preparing a record.
- A task has recognizable inputs and outputs but enough variation that fixed automation alone is awkward.
- The business can limit system permissions and identify actions that always require confirmation.
- A process owner can supply examples, evaluate results, train users, review feedback, and approve changes.
Common questions
Clear answers before you commit.
What can an AI business assistant help with?
A task-specific assistant can help find approved information, summarize documents or conversations, prepare drafts, structure intake, compare records, assemble reports, suggest next steps, and initiate approved workflows. The best use cases have a clear user, input, output, boundary, and review process.
What is the difference between an AI assistant and an AI agent?
An assistant generally helps a person complete work, while an agent may be allowed to choose and execute actions across systems. The labels are used inconsistently, so we define the actual permissions, tools, autonomy, approval points, and stop conditions instead of relying on a product name.
Can an AI assistant connect to our business systems?
Yes, when a suitable API, connector, database, file exchange, or workflow exists. Connections should use the minimum functions and permissions required, validate inputs and outputs, log important actions, and require human approval for sensitive or difficult-to-reverse changes.
Will an AI assistant replace employees?
The goal is to reduce repetitive preparation and retrieval work while keeping accountable decisions with people. A well-designed assistant supports a defined role, makes its sources and limits visible, and hands uncertain or high-impact work to the employee responsible for the outcome.
How do you test an AI assistant?
Testing covers representative tasks, source support, required fields, permissions, tool use, approvals, ambiguous requests, incorrect assumptions, sensitive data, adversarial inputs, failure handling, cost, latency, and the employee's ability to recognize and correct a poor result.
Choose one task where an assistant can prove its value.
Start with the employee, repeated task, current examples, approved systems, and decisions that must stay human. We will map a bounded pilot and the evidence needed before broader use.