AI Copilot Metrics

API endpoints for AI copilot usage, adoption, and productivity metrics

AI Copilot Metrics

AI Copilot metrics measure how developers interact with AI coding assistants, adoption rates, and the impact on productivity across your organization.

Available Metrics

Adoption & Usage

ai-adoption-rate · string

Percentage of active developers using AI tools

adopted-users · string

Number of users who have adopted AI tools

adoption-rate · string

AI tool adoption rate

Suggestions & Acceptance

suggested-lines · string

Lines of code suggested by AI

accepted-lines · string

Lines of code accepted from AI suggestions

ai-acceptance-rate · string

Percentage of AI suggestions that were accepted

acceptance-rate · string

AI suggestion acceptance rate

total-accepts · string

Total number of accepted AI suggestions

total-rejects · string

Total number of rejected AI suggestions

Code Volume

ai-total-loc · string

Total lines of code written with AI assistance

ai-percent-ai-generated-code · string

Percentage of all code that was AI-generated

ai-code-ratio · string

Ratio of AI-generated code to total code

total-lines-added · string

Total lines added with AI assistance

total-lines-deleted · string

Total lines deleted with AI assistance

Requests by Type

chat-requests · string

Number of AI chat requests

composer-requests · string

Number of AI composer requests

agent-requests · string

Number of AI agent requests

cmd-k-usages · string

Number of inline (Cmd+K) AI usages

Quality & Cost

ai-complexity-score · string

Complexity score of AI-assisted code

ai-pr-count · string

Number of pull requests created with AI assistance

ai-total-token-usage · string

Total AI token usage

ai-total-cost · string

Total estimated cost of AI usage

Insights

ai-favourite-model · string

Most used AI model across the organization

most-used-programming-language · string

Most used programming language in AI interactions

Accepted vs Suggested Lines

Retrieve both accepted and suggested lines in a single request to calculate acceptance rate over time.

Request

curl -X POST 'https://api.bilanc.co/metrics/get-multiple-metrics' \
  -H 'Authorization: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "filters": {
      "team": ["team123"],
      "start_date": "2024-01-01",
      "end_date": "2024-03-31"
    },
    "date_level": "month",
    "metrics": ["suggested-lines", "accepted-lines"],
    "date_fields": {
      "suggested-lines": "date",
      "accepted-lines": "date"
    },
    "aggregations": {
      "suggested-lines": "SUM",
      "accepted-lines": "SUM"
    }
  }'

[
  {
    "month_date": "2024-01-01",
    "sum_suggested_lines": 4500,
    "sum_accepted_lines": 3200
  },
  {
    "month_date": "2024-02-01",
    "sum_suggested_lines": 6800,
    "sum_accepted_lines": 4900
  },
  {
    "month_date": "2024-03-01",
    "sum_suggested_lines": 8900,
    "sum_accepted_lines": 6700
  }
]

AI Adoption Rate

Track the percentage of active developers using AI tools over time.

Request

curl -X POST 'https://api.bilanc.co/metrics/ai-adoption-rate' \
  -H 'Authorization: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "filters": {
      "start_date": "2024-01-01",
      "end_date": "2024-03-31"
    },
    "group_by": ["team_name"],
    "date_level": "month",
    "date_field": "date"
  }'

[
  {
    "month_date": "2024-01-01",
    "team_name": "Frontend",
    "ai_adoption_rate": 0.75
  },
  {
    "month_date": "2024-01-01",
    "team_name": "Backend",
    "ai_adoption_rate": 0.60
  },
  {
    "month_date": "2024-02-01",
    "team_name": "Frontend",
    "ai_adoption_rate": 0.82
  },
  {
    "month_date": "2024-02-01",
    "team_name": "Backend",
    "ai_adoption_rate": 0.71
  }
]

Most Used AI Model

Retrieve the most commonly used AI model across the organization.

Request

curl -X POST 'https://api.bilanc.co/metrics/ai-favourite-model' \
  -H 'Authorization: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "filters": {
      "start_date": "2024-01-01",
      "end_date": "2024-03-31"
    },
    "group_by": ["team_name"],
    "date_field": "date"
  }'

[
  {
    "team_name": "Frontend",
    "ai_favourite_model": "claude-3-5-sonnet"
  },
  {
    "team_name": "Backend",
    "ai_favourite_model": "gpt-4o"
  }
]

Parameter Notes

date_field · string

For AI copilot metrics the available date field is:

• date: The date of the AI interaction

aggregation · string

• For line counts and totals: SUM
• For rate metrics (ai-adoption-rate, ai-acceptance-rate, acceptance-rate, adoption-rate, ai-code-ratio, ai-percent-ai-generated-code): no aggregation needed — values are pre-computed percentages/ratios
• For cost and token usage: SUM or AVG

filters · object

Applicable filters for AI copilot metrics:

• ai_copilot_sources: Filter by AI copilot source name (e.g. cursor, github-copilot)
• team: Filter by team IDs
• squad_ids: Filter by squad IDs
• squad_levels: Filter by squad hierarchy level
• manager_ids: Filter by manager user IDs
• departments: Filter by department names
• member: Filter by user merged user IDs
• locations: Filter by employee location
• levels: Filter by employee level

Common Use Cases

• Adoption Monitoring: Track AI tool adoption across teams over time
• ROI Analysis: Compare ai-total-cost against productivity gains
• Acceptance Quality: Monitor acceptance-rate to gauge suggestion relevance
• Language Insights: Use most-used-programming-language to focus AI training
• Usage Breakdown: Compare chat-requests, composer-requests, and agent-requests to understand how developers use AI