Intake Form API

AI-powered project intake and requirements analysis

The Intake Form API processes new project submissions with AI-powered analysis using Claude. It captures client requirements, analyzes project scope, and generates initial proposals automatically.

Submit Intake Form

cURL

curl -X POST "https://bknd.fata.plus/api/intake" \
  -H "Content-Type: application/json" \
  -d '{
    "client_info": {
      "name": "Rakoto Farmer",
      "email": "[e-mail]",
      "phone": "[phone]"
    },
    "project_details": {
      "type": "agri-tech",
      "title": "Smart Irrigation for Rice Fields",
      "description": "Need automated irrigation system for 5 hectares of rice paddy fields",
      "goals": ["Reduce water waste", "Increase yield", "Remote monitoring"],
      "timeline": "3 months",
      "budget_range": "$5000-$10000"
    },
    "farm_details": {
      "crop_type": "rice",
      "farm_size": 5,
      "location": {
        "region": "Alaotra-Mangoro",
        "coordinates": {
          "lat": -17.5,
          "lng": 48.5
        }
      },
      "current_challenges": "Manual irrigation is labor-intensive and inconsistent"
    }
  }'

Submits a new project intake form with AI-powered requirements analysis.

Endpoint: POST /api/intake

Request Body

client_info · object · required

Client contact information

Show Properties

client_info.name · string · required

Client full name

client_info.email · string · required

Client email address

client_info.phone · string

Client phone number

project_details · object · required

Core project information

Show Properties

project_details.type · string · required

Project type: agri-tech, design, or consulting

project_details.title · string · required

Project title

project_details.description · text · required

Detailed project description

project_details.goals · array

Array of project goals and objectives

project_details.timeline · string

Expected project timeline

project_details.budget_range · string

Budget range or estimate

farm_details · object

AgriTech-specific details (required for agri-tech projects)

Show Properties

farm_details.crop_type · string

Type of crop: rice, vanilla, coffee, cassava, etc.

farm_details.farm_size · number

Farm size in hectares

farm_details.location · object

Farm location with region and optional coordinates

farm_details.current_challenges · text

Description of current farming challenges

Response

intake_id · string

Unique identifier for this intake submission

client_id · string

ID of the created or matched client account

project_id · string

ID of the created project (status: pending)

ai_analysis · object

AI-generated analysis and recommendations

Show Analysis Fields

ai_analysis.summary · string

AI-generated project summary

ai_analysis.scope · array

Identified project scope items

ai_analysis.requirements · array

Extracted technical requirements

ai_analysis.recommendations · array

AI recommendations for project success

ai_analysis.estimated_timeline · string

AI-estimated realistic timeline

ai_analysis.risk_factors · array

Identified potential risks or challenges

next_steps · array

Recommended next steps for the client

created_at · datetime

Submission timestamp

Response

{
  "intake_id": "intake_xyz123",
  "client_id": "client_new456",
  "project_id": "proj_abc789",
  "ai_analysis": {
    "summary": "Smart irrigation project for 5-hectare rice farm in Alaotra-Mangoro region requiring IoT sensors, automated water management, and remote monitoring capabilities.",
    "scope": [
      "Soil moisture sensor installation",
      "Weather station integration",
      "Automated valve control system",
      "Mobile monitoring dashboard",
      "Data analytics and reporting"
    ],
    "requirements": [
      "IoT sensors: 10-15 soil moisture sensors",
      "Water flow control: 3-5 automated valves",
      "Connectivity: LoRaWAN or cellular network",
      "Power: Solar panels with battery backup",
      "Software: Mobile app (Android) + web dashboard"
    ],
    "recommendations": [
      "Start with pilot deployment in 1 hectare",
      "Use LoRaWAN for better rural connectivity",
      "Include farmer training program",
      "Plan for seasonal maintenance"
    ],
    "estimated_timeline": "4-5 months (including pilot phase)",
    "risk_factors": [
      "Network connectivity in rural area",
      "Seasonal weather impact on installation",
      "Farmer adoption and training needs"
    ]
  },
  "next_steps": [
    "Schedule site visit and assessment",
    "Review detailed proposal with pricing",
    "Plan pilot deployment phase"
  ],
  "created_at": "2026-03-03T10:30:00Z"
}

AI Integration

The intake form uses Claude AI to:

1. Analyze Requirements: Extract and structure project requirements from natural language descriptions
2. Scope Definition: Identify project scope items and technical needs
3. Risk Assessment: Flag potential challenges and risks
4. Timeline Estimation: Provide realistic timeline estimates based on project complexity
5. Generate Recommendations: Suggest best practices and implementation strategies

Form Processing Flow

1. Client submits intake form with project details
2. System creates or matches client account by email
3. AI analyzes the submission and extracts structured requirements
4. New project is created with status pending
5. Response includes AI analysis and next steps
6. Admin receives notification for follow-up

Use Cases

• AgriTech Projects: Smart irrigation, crop monitoring, marketplace integration
• Design Projects: UX/UI work, Figma design systems, brand development
• Consulting Projects: Strategy, digital transformation, training programs