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AI Response Evaluation
Preference ranking, rubric-based review, factuality checks, style assessment and structured human feedback.
Human-in-the-loop data operations
Human expertise, structured for better AI.
THINKFORM LIMITED helps AI teams build, evaluate and improve intelligent systems through managed expert workflows, multilingual data operations and measurable quality control.
MANAGED WORKFLOW
From requirements to validated data
01Scope
02Qualify
03Produce
04Review
05Deliver
TextEvaluation
AudioTranscription
ImageAnnotation
ExpertReasoning
AI data capabilities
Data operations designed around your model.
We combine qualified people, project management and quality assurance to produce useful, traceable data across the AI lifecycle.
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Data Annotation
Text, image, audio and video classification, tagging, segmentation and quality validation.
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Language & Localisation
Translation review, linguistic evaluation, cultural adaptation and locale-specific data production.
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Speech & Transcription
Speech collection, transcription, speaker labelling, timestamping and audio quality review.
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Data Collection
Consent-based collection of text, images, audio, video and user feedback for defined research use cases.
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Domain Expert Data
Specialist prompts, answers, evaluations and reasoning data produced by qualified professionals.
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Quality Operations
Guideline development, reviewer calibration, sampling, error analysis, rework and delivery reporting.
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Safety & Red-Team Support
Policy-based testing, risk categorisation and structured evaluation for safer model behaviour.
Managed delivery
A clear path from project brief to accepted output.
Every engagement is defined through a written scope, measurable quality criteria and a controlled delivery workflow.
Start a project conversation →Define the assignment
We clarify the data type, language, volume, security needs, acceptance criteria, timeline and commercial structure.
Build the qualified team
Contributors are selected according to language, location, expertise and project-specific qualification requirements.
Train and calibrate
Guidelines, examples, qualification and reviewer calibration align the team before scaled production.
Produce and review
Tasks move through controlled production, automated checks, human QA, exception handling and rework where required.
Deliver and report
Accepted output is delivered with agreed reporting, quality metrics and traceable project records.
For independent professionals
Bring your language, knowledge and judgement to meaningful AI projects.
We invite qualified independent contributors to express interest in project-based opportunities across data evaluation, annotation, collection, transcription, localisation and specialist review.
Language specialistsResearchersIndustry professionalsGeneral contributors
Apply to Our Network1
Introduce yourself
Share your location, languages, skills, professional background and availability.
2
Complete qualification
Eligible applicants may be invited to identity checks, training or project-specific assessments.
3
Receive project invitations
Assignments are offered according to project demand and your verified profile.
4
Submit and get reviewed
Completed work is assessed against documented quality and acceptance standards.
5
Receive payment
Accepted work is settled under the applicable contractor agreement and project terms.
Application does not guarantee project placement. Project availability, eligibility, rates and timing vary by assignment and jurisdiction.
Trust & quality
Designed for accountable human data production.
Our operating model is built around clear responsibilities, controlled participation and evidence-based quality decisions.
Identity and eligibility checks
Contributor information and payment details are reviewed according to project and jurisdiction requirements.
Contract-based assignments
Project scope, compensation basis, confidentiality and intellectual property terms are documented before work begins.
Controlled access
Project access is limited to approved participants, with rules governing data handling and permitted tools.
Layered quality review
Calibration, sampling, reviewer checks, error analysis and rework support consistent acceptance decisions.
Traceable settlement
Contributor payments are linked to project records, accepted work and documented calculations.
Continuous improvement
Feedback loops refine instructions, identify recurring issues and improve delivery across project stages.
Start the conversation
Connect With UsHave an AI data project—or expertise to contribute?
Tell us what you need or how you would like to participate. Our team will review your submission and follow up where there is a suitable match.