System execution
The system handles organization, decisions, and cross-system handoffs when rules are relatively stable and repeatably testable.
Service facts · Citable service facts
Enterprise AI Workflow System Design and Delivery
For small and medium businesses dealing with repetitive manual work, cross-system handoffs, or unstructured information. We diagnose the real workflow, define human review, recovery, and acceptance, then deliver a custom AI automation system designed for day-to-day operation.
When an initial diagnosis makes sense
- High-frequency workflows with relatively stable rules that move across files or systems
- Workflows where AI handles unstructured information while critical results still require human review
- Automation that must preserve state, exceptions, recovery records, and auditable outputs
What we need before starting
- The actual workflow steps, frequency, and owners
- Input, output, and exception samples available for validation
- Key decisions or high-risk actions that must remain under human confirmation
01 / Operating model
What the system handles, what people retain
Human review
Key decisions, high-risk actions, and exceptions retain explicit human confirmation and takeover points.
Delivery evidence
Delivery includes a working system, operating boundaries, and traceable records for status, exceptions, recovery, and outputs.
02 / Delivery method
From a real workflow to a working delivery
Features, schedule, and deliverables are determined through workflow diagnosis and validation with real samples; an initial submission is not an automatic quote.
Diagnose the current workflow
Map real inputs, processing steps, owners, exceptions, and deliverable outcomes.
Design the human boundary
Define what AI may handle, who reviews critical decisions, and which actions require confirmation.
Validate the real workflow
Validate inputs, exceptions, recovery, review, and outputs with real samples rather than an idealized demo path.
Deliver and improve
Deliver a working system, operating boundaries, and traceable evidence, then improve it from real use.
03 / Delivery contract
Standard deliverables and acceptance evidence
The exact scope varies by engagement, but every delivery should show whether the system works, who reviews critical decisions, how failures recover, and which real samples define acceptance.
- 01
Current workflow and system boundary
Map steps, owners, inputs, outputs, and exceptions, including what the system handles and what people retain.
- 02
Working system and deployment result
Deliver a working system, or an agreed reproducible deployment package, configuration, and operating entry point—not only a presentation.
- 03
Operating guide and human review points
Document routine operation, required access, human confirmation, exception takeover, and ownership.
- 04
Exception and recovery path
Preserve exception records, checkpoints, and retry or human takeover paths so an interruption does not require restarting from scratch.
- 05
Acceptance samples and result records
Use agreed real samples to record expected and actual results, exceptions, and traceable outputs.
- 06
Handover and support scope
Define system ownership, maintenance, change scope, and follow-up support in the engagement without implying a default service-level commitment.
04 / Operating boundary
Data, permission, and operating boundaries
Data and access are part of solution design and acceptance, not an appendix after delivery. These items must be agreed against the real operating environment before implementation.
Necessary data and real samples
Request only the samples needed to validate the real workflow, with sensitivity, purpose, and permitted use agreed before work starts.
Deployment and processing location
Local, private, or cloud deployment is chosen from the company's systems, data requirements, and operating conditions rather than a blanket promise.
Least privilege and account control
The system uses only access needed for the agreed workflow; where practical, the company retains control of accounts, tokens, and final authorization.
Retention, backups, and deletion
Retention periods, copies, backups, and deletion are defined per engagement; unspecified handling is not treated as a default commitment.
Human authorization for high-risk actions
External sending, payment, publication, and other high-risk actions must retain human authorization or an explicit approval point.
Compliance and security claims
Technical implementation is not presented as a legal compliance conclusion or security certification without the relevant agreement, review, or certification.
05 / Business scenarios
Explore deliverable systems by concrete business problem
Start from AI search visibility, enterprise knowledge, Google Maps prospecting, or Feishu collaboration, then review system scope, human boundaries, and delivery evidence.
AI search visibility diagnosis and remediation
Open GEO Console
Diagnoses an enterprise website's visibility in AI search, turning technical foundations, buyer questions, public answers, and citation evidence into an executive report and a vendor task package.
View system and evidenceEnterprise data engine for AI applications
Hermes Notebook
Turns enterprise information scattered across PDFs, Word, Excel, PowerPoint, images, local folders, and business web pages into citable, retrievable knowledge that can support customer-service bots, internal Q&A, and other business assistants through APIs.
View system and evidenceGoogle Maps prospecting and personalized outreach
Freight Lead Agent
Finds target companies through Google Maps, reads each official website for business context and public contacts, prepares personalized outreach from that context, and carries it through review, sending, and reply follow-up.
View system and evidenceEnterprise AI collaboration system
Codex Feishu Bridge
Connects Codex to an enterprise Feishu workspace. Members can submit questions, files, and long-running tasks from a computer or phone, then add context, check status, and receive deliverables after leaving their desks while an online company workstation continues the execution.
View system and evidenceClear boundaries
- No fixed industry templates are sold; every engagement starts from the actual workflow.
- Not every step is promised to be unattended; critical decisions and high-risk actions retain human review.
- No invented metrics, customer identities, or unapproved project outcomes are used as sales proof.
- An initial submission is not an automatic quote or a guaranteed meeting.
Reviewed evidence
Review verified facts before deciding whether it fits
The project library only publishes reviewed facts. Projects without public review are not used as sales proof.
View project evidence05 / Buyer questions
Frequently asked questions before buying
Judge the workflow and delivery model before comparing tools or providers.
Read the complete provider selection and acceptance checklist- Which companies should start with an AI automation diagnosis?
- High-frequency workflows with relatively stable rules, cross-file or cross-system handoffs, repeated judgment, exception handling, or weak traceability are usually worth diagnosing. The goal is to determine fit, not to assume AI must be added.
- Should a small or medium business choose SaaS, RPA, or a custom system?
- Start with SaaS when the workflow is standard and product boundaries are acceptable; evaluate RPA for stable interfaces and explicit repetitive rules; consider a custom system when work crosses systems, includes unstructured information, and requires human review and recovery. Diagnose the workflow before choosing the technology.
- What should a buyer verify when choosing an AI system provider?
- Verify whether the provider can reproduce the workflow with real samples and clearly define human boundaries, deliverables, exception recovery, data access, acceptance, and follow-up support. Cases, customer identities, and metrics should also be verifiable—not just demonstrated.
- How are schedule and price determined?
- Schedule and price depend on workflow diagnosis, the number of system integrations, sample and exception complexity, deployment requirements, and acceptance scope. An initial submission is for fit assessment, not an automatic quote.
- Is full automation or a guaranteed business result promised?
- No promise is made that every step will be unattended, and no improvement percentage is invented. Critical decisions and high-risk actions retain human review; results depend on the workflow, data, use, and agreed acceptance criteria.
Start with one specific workflow
Submit the current workflow, frequency, manual effort, and exception samples. We will contact you by work email only when further diagnosis makes sense.