Use Case
About Agentitek
Agentitek is a workflow-delivery service for small teams that need deployable AI Agent systems, not vague AI strategy decks.
Who we serve
- Small teams that already have repeatable workflows and want a deployable first delivery
- Operators who need business rules and human-review boundaries made explicit before implementation
- Owners who care whether a workflow is reviewable, maintainable, and iterable after delivery
What we deliver
- Agent Spec and workflow design
- Tested system prompts and test cases
- Platform adapter guidance for the chosen runtime
- User guidance for review, rollout, and acceptance
What we do not do
- We do not position Agentitek as a full SaaS platform
- We do not promise autonomous handling of high-risk decisions
- We do not invent proof, testimonials, or metrics to close deals
How clients work with us
- Start with a workflow assessment
- Define scope, boundaries, and acceptance criteria
- Receive a delivery package built for a target platform
- Review, test, and decide whether to deploy or iterate
Publicly verifiable trust signals
This page should not invent founder prestige. It should show what can actually be checked in public today.
Public project and delivery assets
- Public GitHub repository: github.com/RichardGitHub/agent-factory
- Public pages explain the delivery method, quality threshold, deliverable samples, and multiple use cases.
- The repo exposes Agent Spec assets, platform adapters, testing templates, and risk-boundary material instead of only marketing copy.
Delivery background
- The current public work centers on turning repetitive business processes into deployable, testable, maintainable workflow packages.
- Public use cases already cover customer FAQ, email triage, content publishing, internal reporting, and lead scoring workflows.
- The delivery scope is spec, workflow, tests, platform adapter, and user guide rather than prompt-only output.
Why this is credible
- The public site explicitly states what it does not do, including autonomous payment, refund, contract signing, and regulated final decisions.
- The public site also exposes a quality threshold instead of relying on vague “AI agent capability” claims.
- Boundaries, escalation rules, and test examples help a buyer judge that this is not an empty-shell AI site.
Identity boundary
The strongest current public signal is the repository plus the methodology, sample, and boundary pages. Social profiles beyond GitHub should only be added when they are real and actively maintained, not fabricated for E-E-A-T theater.
Why workflow-first matters
Many AI service sites still sell prompts. Agentitek treats workflow-first delivery as part of the trust model because the buyer has to inherit a process, not a temporary text artifact.
Why not prompt-first
- A single prompt does not explain input boundaries, exception paths, human review points, or acceptance rules.
- Workflow-first delivery defines steps, branches, escalation conditions, and forbidden actions before prompt writing.
- That makes the package reviewable, testable, and maintainable after handoff.
Delivery lens vs implementation lens
- An implementation-first team often jumps directly into code or model calls.
- A delivery-first team asks who inputs data, who approves, where failures occur, and what must always escalate.
- That is why Agentitek is positioned as a workflow delivery service rather than a generic AI outsourcing site.
Confidentiality, NDA, and human contact path
A stronger About page answers not just what the service does, but how sensitive materials are handled and how a real human is reached.
Client confidentiality and material handling
- Prefer anonymized examples and minimum-necessary materials.
- Sensitive customer messages, risk judgments, and exception rules keep explicit human-review boundaries.
- Detailed handling rules are published on the Data Handling & Privacy page.
NDA and contract boundary
If a workflow involves sensitive samples, internal systems, or restricted materials, NDA terms, contract scope, access boundaries, and redaction rules should be confirmed before detailed materials are shared. This is treated as an operational precondition, not a slogan.
How to contact a real human
- The current public entry point is the workflow assessment form.
- The public response commitment on the site is within 24 hours on working days.
- The best first contact includes the current manual process, desired outcome, constraints, and budget band.
How to judge whether this is an empty-shell AI site
- Check the public GitHub repository first.
- Then compare Delivery Method, Quality Score, Samples, and Privacy pages for consistency.
- Finally, look at whether the site is willing to state what it will not do and how confidentiality is handled.