Quality & Trust Guide

Cognowork • Powered by Kwava UK Limited

Choosing the right expert can define your project’s success. At Cognowork, we invest in careful vetting, clear processes, and practical tools so clients connect with skilled AI professionals—and experts can do their best work with confidence.

Version: 1.0 • Updated: 02 Oct 2025

Community Principles

Our community principles

Professional conduct and respectful collaboration—no harassment or discrimination.
Honest communication, clear scopes, and on-time delivery with milestone visibility.
Confidentiality and data protection, with secure on‑platform tools and NDAs where needed.
Accessibility-minded outputs (e.g., alt text, readable layouts).
Use of rights‑cleared assets and accurate citations.

Cognowork Framework

Cognowork’s four pillars of quality

Proven skills

Experts are assessed on craftsmanship and outcomes across AI categories. Clear briefs and scope increase the odds of a great result.

Data Engineering ML Engineering LLM App Dev PromptOps Evaluation & Red Teaming Agents & Automation MLOps / LLMOps AI Analytics

Clear communication

Responsive messaging, aligned expectations, and milestone updates ensure you always know what’s happening and what comes next.

Professional presentation

Complete profiles with portfolios, case studies, and (where relevant) demos help you evaluate fit before you commit.

Standards & compliance

Work adheres to relevant technical and legal specs (data privacy, licensing, brand guidelines, and evaluation standards), plus Cognowork policies and local laws.

Discovery

How we highlight quality experts

Transparent signals: Ratings, reviews, and project history help identify consistent performers.
Smart matching: Filters, categories, and brief templates route work to the right specialists. Choose Direct Order or Bidding to compare approaches.
Category gating: Sensitive domains (e.g., medical/financial or regulated data) may require extra checks or credentials.
Optional editorial QA: For certain workflows, an editor can review deliverables before client handoff.

Quality Assurance

Multiple layers of quality assurance

Risk checks: Automated and manual reviews help detect fraudulent activity early.
Marketplace integrity: Repeated policy violations or trust breaches lead to restrictions or removal.
Support when needed: If disagreements arise, Cognowork Support helps resolve issues fairly.
Continuous improvement: Resources, templates, and best practices help experts raise their game.

Expectations

What clients and experts can expect

Clients

Clear scopes and acceptance criteria.
Reliable timelines and milestone transparency.
Organized files and versioning.
Structured revisions and predictable payment options.

AI Experts

Fair briefs and realistic budgets.
Responsive feedback and respectful collaboration.
Security, privacy, and IP clarity.
Recognition for consistent, high‑quality delivery.