Scope of deliverables
Plan AI-assisted workflows with clear triggers, approval gates, error fallbacks, and measurable acceptance criteria.
Verified project deliverables
- Workflow discovery & bottleneck mapping
- API & webhook connectivity architecture
- Human-in-the-loop approval gates
- Deterministic fallback & exception routes
- Zero-data-retention security configuration
- Pilot evaluation, ROI baseline & handover
Real-world workflow automation use cases
Effective automation focuses on well-defined repetitive tasks rather than vague conversational chatbots. We design and implement production workflows across key operational functions:
Key specifications & considerations
- Inbound Lead Triage & CRM Routing: Ingest incoming form inquiries or emails, classify intent, extract budget/timeline parameters into structured CRM fields, and draft personalized responses for human sales reps to review and send.
- Document & Invoice Extraction: Optical and multimodal parsing of vendor invoices, PDF receipts, and service agreements directly into structured accounting records (QuickBooks, Xero, Airtable) with confidence-score validation.
- Customer Support Ticket Summarization: Group incoming support tickets by urgency and category, extract relevant account details from internal databases, and present agents with synthesized context before they reply.
- Automated Meeting Summaries & Action Items: Process meeting transcripts into action items, assign owners, and stage tasks in Linear, Jira, or Asana following manager approval.
Keep people in control of consequential actions
AI models can hallucinate or misinterpret ambiguous requests. Our engineering methodology separates AI drafting from execution permissions. Consequential actions—such as sending customer emails, modifying accounting ledgers, or updating production records—remain behind human approval gates.
Key specifications & considerations
- Human approval gates for sensitive or irreversible actions
- Structured JSON schema validation to prevent unexpected outputs
- Automatic fallback to human operators when confidence scores fall below threshold
- Comprehensive audit logging for all automated decisions and handoffs
Strict data privacy and zero model training
Your proprietary business documents, customer communications, and financial records must never be exposed to public AI training datasets. We connect workflows using enterprise API tiers with explicit zero-data-retention (ZDR) contractual terms and enforce least-privilege API access.
Key specifications & considerations
- Zero-data-retention (ZDR) agreements with enterprise API providers
- Automated sanitization of personally identifiable information (PII)
- Encrypted credentials and secrets stored in dedicated key management vaults
- Strict data retention windows and isolated execution environments
Measure the pilot before expanding operations
We evaluate every automation against historical operational baselines using your actual sanitized records. We track real metrics: active handling time reduction, human correction rate, and API unit consumption costs rather than assuming theoretical savings.
Key specifications & considerations
- Side-by-side time and accuracy benchmarking against manual processing
- Clear unit economics tracking per task execution
- Documented runbooks, operational manuals, and team handover sessions
What to prepare before we begin
Prepare a written outline of the repetitive task, the specific applications involved (e.g. Gmail, Slack, HubSpot, Airtable), approximate monthly task volume, and representative sanitized examples. Identify which person approves outputs. Email your brief to simkieu@gmail.com without including private credentials.
Direct contact for project inquiries: +1 669 777 6562 simkieu@gmail.com
Frequently asked questions
How do we prevent AI errors or hallucinations in automated workflows?
We employ a defense-in-depth approach: strict prompt boundaries, retrieval-augmented grounding from approved documentation, JSON schema validation for all outputs, and human review gates for any action that affects customers or financial records.
Will our company data be used to train public AI models?
No. We implement commercial enterprise API endpoints (Anthropic, OpenAI, or Google Cloud Vertex AI) governed by strict zero-data-retention agreements where client data is never stored or used for model training.
Which tools and software can be integrated?
Any platform providing standard REST APIs, webhooks, or database interfaces can be connected, including Google Workspace, Microsoft 365, Slack, HubSpot, Salesforce, Airtable, Notion, Stripe, and custom internal SQL databases.
How does a typical pilot project start?
We begin with a 2-week discovery and pilot phase focusing on a single, high-friction workflow. We establish baseline metrics, build the integration with human oversight, and evaluate real time savings before expanding to other departments.
Planning resources
AI automation
AI workflow automation for small businesses: where to start
Choose a practical first AI workflow for your small business. Map the task, compare rules with AI, define human review and plan a limited pilot before scaling.
Read the guideAI evaluation
How to evaluate an AI automation pilot
Evaluate an AI automation pilot using baseline task time, review effort, corrections, quality checks and operating costs, with an illustrative planning calculator.
Read the guide