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TechAI Remote

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Empowering AI Remotely

Tech AI Remote provides specialized data annotation services for computer vision and AI systems where accuracy determines production deployment success. Based in Nairobi with a team of 50+ trained annotation specialists, we handle complex labeling tasks across image, video, text, and 3D point cloud data.

  • Min project size
    $1,000+
  • Hourly rate
    $25 - $49 / hr
  • Employees
    50 - 249
  • Year founded
    Founded 2022

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    Our Story

    Built to solve the lab-to-production gap in computer vision. AI models hitting 95% accuracy in controlled environments, then dropping to 60% in real-world deployment because training data couldn't handle edge cases.

    We're a team of 50+ annotation specialists in Nairobi who focus on what breaks automation - weather-obscured license plates, warehouse clutter, complex security footage. 

    We handle the 5% that determines whether your model ships or stays in the lab.

    What Sets Us Apart

    Edge Case Specialists, Not Volume Players

    We focus on the 5% of annotations where automation fails. Our team handles weather-obscured license plates, warehouse clutter for robotics, and security footage requiring contextual judgment. We've annotated 100,000+ edge cases across autonomous systems, robotics, and computer vision applications.

    98.5% QA Accuracy Guaranteed

    Four-stage QA process on every project: annotator calibration, production with automated checks, peer review on 20-30% of batches, and final QA validation. We maintain 98.5% accuracy with 94-97% inter-annotator agreement. You receive detailed QA reports.

    Direct Team Access, No Middlemen

    Work directly with annotators, not account managers. We ask informed questions about your model and edge cases, move fast, and tell you straight if we're not the right fit. Free pilots on 200-1500 samples let you verify quality first.

    Quick Facts

    3 years in business

    Team Breakdown

    Project Management & Client Success (3)
    Computer Vision Annotation Team (30)
    Edge Case Specialists (70)
    Quality Assurance Team (10)

    Tools and Technology

    Slack
    Google Meet
    Discord
    OneDrive
    Dropbox
    Google Docs
    Google Sheets
    Google Slides
    GitHub

    Commonly Asked Questions

    Clients save 40-50% on annotation costs compared to hiring in-house teams, while maintaining higher quality than offshore crowdsourced alternatives. Average project completion is 2-3 weeks faster than industry standard due to our streamlined QA process and direct team communication. 94% client retention rate - most pilots convert to production contracts within 48 hours of completion.

    Initial Consultation (15-30 min): Direct call with annotation team lead to understand your data type, edge cases, model architecture, and accuracy requirements. We assess fit and provide upfront guidance on expected turnaround and pricing. Free Pilot Setup (24-48 hours): You send 200-500 sample items. We develop custom annotation guidelines, train annotators on your specific requirements, and run calibration tests to ensure 95%+ accuracy before production work begins. Pilot Delivery (3-5 days): Annotated samples delivered with QA report showing accuracy metrics, inter-annotator agreement scores, and flagged edge cases. You review quality and provide feedback. Guideline Refinement (1-2 days): We incorporate your feedback, adjust guidelines, and re-train annotators on specific edge cases or corrections identified during pilot review. Production Launch (immediate): Once you approve pilot quality, production batches begin. Most clients book their first production contract within 48 hours of pilot completion. Ongoing: Direct Slack/email communication with annotation team throughout project. Weekly delivery cadence with continuous QA reporting and iterative guideline updates as new edge cases emerge. Average time from first call to production delivery: 7-10 days.

    High Priority: Robotics perception systems requiring edge case handling (warehouse automation, manipulation tasks, bin-picking in cluttered environments) Autonomous vehicle datasets with challenging conditions (weather occlusion, night vision, dense urban scenes) Security and surveillance applications requiring contextual reasoning (identity tracking, event classification, anomaly detection) Computer vision systems transitioning from lab to production where automated labeling accuracy has plateaued Good Fit: 3D point cloud and LiDAR annotation for navigation and spatial AI License plate recognition systems across multiple regions/conditions Manufacturing defect detection requiring domain expertise Medical imaging annotation where accuracy is critical Custom sensor fusion validation projects Project Characteristics We Prefer: 5,000+ items needing annotation (or ongoing monthly volume) Edge cases present in the dataset that break standard automation Projects valuing accuracy over pure speed Clients who need direct team communication and iterative guideline refinement Not Currently Taking: Pure crowdsourced volume work with no complexity premium Single-batch projects under 500 items (unless testing for larger engagement) Projects requiring sub-24-hour turnaround on large volumes

    Direct Access: You communicate directly with the annotation team and project leads via email or Slack - no account managers or middlemen. Questions about edge cases, guideline clarifications, or quality concerns get answered by people actually doing the work. Project Kickoff: Initial call to align on annotation requirements, discuss edge case priorities, and establish delivery cadence. We ask informed questions about your model architecture and use case to ensure guidelines match your training objectives. During Production: Real-time updates on batch progress and any blockers encountered Proactive flagging of ambiguous cases or edge case patterns not covered in initial guidelines Direct annotator access for technical clarification on complex scenarios Delivery Reporting: QA metrics with every batch: overall accuracy, inter-annotator agreement scores, first-pass acceptance rate Detailed uncertainty flags and annotator reasoning notes for ambiguous annotations Edge case summaries showing distribution of challenging scenarios in each batch Feedback Loops: We incorporate your feedback within 24-48 hours - guideline updates, retraining on specific errors, or annotation corrections. Continuous improvement throughout project lifecycle. Cadence: Weekly deliveries standard. Daily check-ins available for time-sensitive projects.

    Data Security & Privacy: NDAs standard on all projects before data transfer Secure file transfer protocols (SFTP, encrypted cloud storage with access controls) Annotator access logging and audit trails for all data handling Data retention policies customizable per client requirements - automatic deletion post-project or secure archival as specified GDPR Compliance: Data processing agreements available for EU clients Personal data handling protocols aligned with GDPR requirements Data subject rights procedures (access, deletion, portability) implemented on request Cross-border data transfer safeguards for international projects HIPAA: Currently not HIPAA-certified but can work with de-identified medical imaging datasets that don't contain PHI (Protected Health Information) For projects requiring HIPAA compliance, we can discuss BAA execution and infrastructure upgrades on a case-by-case basis Additional Security Measures: Annotator confidentiality agreements and security training On-premise annotation capability available for highly sensitive datasets where data cannot leave client infrastructure Network security and endpoint protection on all annotation workstations We prioritize client data security and can adapt our protocols to meet specific regulatory or compliance requirements for your industry.

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