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- Tasks: Build an AI-powered platform for tender collaboration and streamline expert input collection.
- Company: Innovative tech project focused on enhancing procurement processes.
- Benefits: Competitive pay, flexible work environment, and potential for future projects.
- Why this job: Join a cutting-edge project that transforms how tenders are managed with AI technology.
- Qualifications: Experience in web development, JavaScript, React, and AI integration required.
- Other info: Opportunity for growth and expansion after successful project delivery.
The predicted salary is between 36000 - 60000 £ per year.
I am looking for an experienced software developer or small development team to build a web-based AI-powered collaboration and questionnaire platform for professional tender and procurement processes.
I work with multiple expert partners on public tenders. For each tender, we must develop structured quality plans based on defined criteria. Currently, gathering expert input is manual, fragmented, and inefficient. I want to fully streamline and professionalise this workflow with a dedicated AI-assisted platform.
This project is to build a first production-ready version of the platform — not a prototype — that is already fully usable in practice. After delivery, we will run a structured improvement round based on real usage feedback. This improvement round must be included in your price. No hidden or post-delivery surprise costs.
Core ObjectiveBuild a secure AI-supported platform where:
- Tender documents and context are uploaded
- The system generates structured questionnaires per criterion
- Multiple experts are invited to respond
- AI conducts guided follow-up questioning during answering
- All responses are analysed using AI
- The system produces structured insights and session preparation outputs
The tool must significantly improve the quality, speed, and structure of expert input collection.
Required Core Features- Tender Workspace Creation
Admin can create a workspace per tender with:
- Tender name
- Criteria and sub-criteria structure
- Focus themes and objectives
- Context notes
- Deadlines
- Participant roles
Document upload support:
- Word
- Excel
- Multiple files per workspace
Documents must be processed and usable by the AI layer.
- AI-Based Questionnaire Generation
Per criterion, the system must:
- Generate structured questionnaires using:
- uploaded documents
- admin context
- example seed questions
- Allow admin editing:
- add/remove questions
- reorder
- mark priority questions
- Interactive AI Follow-Up Dialogue
When participants answer questions:
- The AI must:
- Ask intelligent follow-up questions
- Detect vague or incomplete answers
- Ask for clarification, examples, risks, implementation details, measurability
- Create a guided but controlled dialogue
- Avoid endless loops
- Use configurable "depth level"
This is a key differentiator of the platform.
- Multi-Participant Input System
• Invite participants via secure link
• Role-based access
• Each participant submits independently
• Answers stored per user
• Progress tracking
• Editable until submission lock
- AI Analysis Engine
After responses are completed, AI must generate:
- Consensus points across participants
- Conflicting viewpoints
- Missing or weak areas
- Recurring themes
- Risk signals
- Notable insights
Must use semantic comparison — not keyword matching only.
- Session Preparation Output
The system produces structured output for working sessions:
- Key discussion topics
- Clarification questions
- Decision points
- Risk areas
- Alignment opportunities
Export options:
- Word
- Structured on-screen report
- Admin Dashboard
Dashboard must show:
- Participant progress
- Completion status per criterion
- Flagged inconsistencies
- AI insight indicators
- Response completeness scoring
Question sets must be dynamic and AI-assisted, not static forms.
Developer must integrate LLM capabilities for:
- Document understanding
- Question generation
- Follow-up questioning
- Thematic clustering
- Conflict detection
- Insight summarisation
Open to:
- OpenAI API
- Anthropic
- Comparable LLM providers
Architecture must be modular and replaceable.
Technical ExpectationsYou may propose stack, but preferred direction:
- Modern web app (React / or similar)
- API backend
- AI API integration layer
- Secure document storage
- Role-based authentication
- GDPR-aware data handling
- Modular prompt and AI workflow design
Clean architecture is important — this tool will grow.
Delivery Scope Requirement (Important)This project must include:
- Phase 1 — Full Working Version
A fully usable production-ready first version including all core features listed above.
- Phase 2 — Improvement Iteration (Included in Price)
After initial usage and feedback:
- UX refinements
- Prompt tuning
- Flow improvements
- Small functional adjustments
- Stability improvements
This iteration round must be included in your fixed project price. No hidden backend costs. No surprise post-delivery fees.
- Prototype-only builds
- UI mockups without backend intelligence
- Simple form builders
- Chatbot-only solutions without structured workflow
- Developers without real AI integration experience
- Proven experience with AI-powered applications
- Experience with LLM integrations
- Experience building workflow or knowledge platforms
- Strong UX thinking
- Secure architecture mindset
- Able to translate functional concepts into real tools
- Good English communication
Please include:
- Relevant AI application examples
- Suggested technical stack
- Architecture approach
- Estimated timeline
- Fixed total price including iteration round
- What is explicitly included vs excluded
If this first build is successful, follow-up expansion work is very likely.
Contract duration of less than 1 month.
Mandatory skills: Web Development, JavaScript, React, API, Artificial Intelligence
AI-Powered Tender Collaboration employer: FreelanceJobs
Contact Detail:
FreelanceJobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI-Powered Tender Collaboration
✨Tip Number 1
Network like a pro! Reach out to your connections and let them know you're on the hunt for opportunities. You never know who might have a lead or can introduce you to someone in the industry.
✨Tip Number 2
Nail that interview prep! Research the company, understand their projects, and be ready to discuss how your skills can help them achieve their goals. Practice common interview questions and have your own ready to ask.
✨Tip Number 3
Showcase your work! If you've got a portfolio or examples of past projects, bring them along to interviews. This is your chance to demonstrate your skills and how you can contribute to their team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace AI-Powered Tender Collaboration
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with AI-powered applications and LLM integrations. We want to see how your skills align with our project needs, so don’t hold back!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about what you can bring to the table.
Include Relevant Examples: Don’t forget to showcase relevant AI application examples in your proposal. This helps us understand your past work and how it relates to what we’re looking for.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way to ensure your application gets the attention it deserves!
How to prepare for a job interview at FreelanceJobs
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description, especially React and API integrations. Brush up on your knowledge of AI applications and how they can enhance user experience. Being able to discuss specific technologies and their benefits will show that you're not just familiar but also passionate about the tools you'll be using.
✨Prepare Real-World Examples
Have a few solid examples ready that showcase your experience with AI-powered applications and workflow platforms. Be prepared to explain how you’ve tackled challenges in previous projects, particularly those involving LLM integrations or secure architecture. This will help demonstrate your problem-solving skills and practical knowledge.
✨Understand the Project Goals
Familiarise yourself with the core objectives of the project. Understand what it means to streamline tender processes and how an AI-assisted platform can improve efficiency. Showing that you grasp the bigger picture will impress interviewers and highlight your strategic thinking.
✨Ask Insightful Questions
Prepare thoughtful questions about the project, such as how feedback will be gathered post-delivery or what specific challenges they anticipate during development. This not only shows your interest in the role but also your proactive approach to understanding the project’s needs and potential hurdles.
