long story short
At Rebbix, we understand that getting an accurate project estimate is often the first major challenge for potential clients. Traditionally, this process requires lengthy discovery calls, multiple follow-up conversations, and several days of back-and-forth before clients can even understand the scope and budget of their project.
For non-technical founders or stakeholders with a new idea, getting an initial estimate means either finding a technical expert to consult, scheduling calls with multiple development agencies (each trying to upsell their services), or using their existing team's time for exploratory work. All of these options are time-consuming and often overwhelming.
We set out to solve this problem by building an automated project estimation calculator powered by AI. Our goal was to enable potential clients to receive a high-quality, preliminary project estimate in just 90 seconds by answering 5-7 simple questions, rather than spending hours in meetings and correspondence.
However, our goal wasn’t just to automate the process. We wanted to ensure that the estimates were accurate, comprehensive, and reflected our actual development approach, tech stack preferences, and years of experience in the domains we’re working with.
In 1,5 months, our team developed a multi-agent AI workflow that breaks down the estimation process into small, precise steps. We started building our system in n8n for rapid prototyping before migrating to a custom self-hosted application for greater control and scalability. Unlike simply asking ChatGPT for an estimate (which produces wildly inconsistent results ranging from weeks to months for the same project), our system incorporates:
- domain research capabilities – the AI agent can visit and analyze a client's existing platform to understand their business model and technical requirements
- validated timelines – based on the information from our real project portfolio to ensure estimates reflect actual development time
- comprehensive outputs – generating project descriptions, technical architecture, technology recommendations, team composition, and milestone breakdowns
The system works by accepting minimal input through a custom form, then running parallel specialized AI-based workflows that handle different aspects of the estimate: overall project description, technical architecture, technology selection, and timeline validation. Each agent works with small, precise tasks to avoid AI "hallucinations" and ensure logical consistency.
For now, our project continues to evolve with planned features including an AI chatbot to gather information needed for project estimations, an interactive refinement feature for clients to adjust any factors in the estimation they receive and immediately see an updated project assessment, and a potential launch of our calculator as a standalone product.
key outcomes
90 seconds
for potential clients to get an accurate project estimate instead of spending hours in meetings
99%
time reduction for estimate creation - from 2 days to minutes
resource optimization
automated estimates freed up the time of our highly-skilled tech specialists to focus on actual development
flexibility
minutes instead of days to revise estimates when potential clients want to adjust project scope
competitive advantage
immediate value delivered to potential clients, increasing engagement and conversion likelihood
client testimonial
team setup
1
Backend Developer
1
Full-stack Developer
meet the team
what we did
- Researched and identified the minimum set of questions (5-7) needed to generate accurate estimates across different project types
- Built a flexible CMS-based form that allows quick configuration for different project types with integrated sales and marketing tracking
- Developed a multi-agent AI workflow with six specialized sub-workflows, each handling a specific aspect of the estimation (project description, technical architecture, technology recommendations, timeline, team composition)
- Implemented domain research capabilities, allowing the AI to visit and analyze existing platforms to understand business models and technical requirements
- Created a validation layer incorporating our real project history and preferred technology stack to ensure estimates reflect real development timelines
- Ensured the generation of comprehensive artifacts, including project descriptions, technical specifications, milestone breakdowns, and technology recommendations
tools and technologies
- TypeScript
- Express
- React
- Firestore
- Multiple OpenAI models
- n8n (for initial MVP)
- custom Node.js application (current development)
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