Ayomide A.

Key Skills

Software

Other

Top Subject Matter

Conversational AI

CRM automation

lead qualification decision logic

Top Data Types

Text

Document

Top Task Types

Question Answering

Freelancer Overview

Founder / Lead Automation Builder — HiveWorks (AI receptionists and scored decision systems). Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Founder / Lead Automation Builder, HiveWorks (2024) and Freelance CRM & Automation Specialist, Upwork / Fiverr (2024). AI-training focus includes data types such as Text and Document and labeling workflows including Evaluation, Rating, and Question Answering.

Labeling Experience

Freelance CRM & Automation Specialist — Upwork / Fiverr (rule-following automation accuracy & QA)

OtherDocumentQuestion Answering

Delivered technical CRM and automation builds where domain-specific rules and compliance language required careful verification of automated outputs. Configured SaaS infrastructure and validation paths that effectively depend on accurate handling of authentication, permissions, and integration data flows. While not described as dataset labeling, the work includes training-adjacent evaluation and QA of rule-following behaviors to meet exact client specifications.• Verified that automated outputs matched detailed client specifications and compliance constraints• Reviewed and corrected workflow logic tied to integration/authentication data paths• Ensured accurate handling of domain-specific rules for healthcare, franchise, and membership contexts• Collaborated asynchronously with clients to iterate on accuracy and reliability requirements

2024 - Present

Founder / Lead Automation Builder — HiveWorks (AI receptionists and scored decision systems)

Text

Built and tuned AI receptionist conversational systems for service businesses, using iterative testing to assess response accuracy and tone across real-world scenarios. Conducted structured evaluation of input/output quality for scored lead-qualification and decision-tree branches, identifying logic errors and edge cases. Produced rubric-aligned feedback and clear, structured documentation to guide non-technical stakeholders on automated system behavior and quality criteria.• Evaluated automated conversation responses for correctness, completeness, and appropriate tone• Tested decision-tree and workflow logic at each branch to find failure points• Refined prompts/conversation flows based on observed inaccuracies and edge cases• Documented evaluation rationale and system behavior using structured task guidelines

2024 - Present

Education

Work History