AI Features

Velocity includes built-in AI capabilities powered by a provider-agnostic LLM gateway. Features range from smart search to autonomous agents, with usage tracking and a monthly credit allowance per seat.

Overview

AI features in Velocity are plan-gated and can be enabled or disabled per workspace. Every AI call is tracked for token usage and cost. A workspace's monthly AI allowance is its seats times the plan's credits per seat.

Highlights

Available Features

Plan Tiers & AI Credits

Each plan includes a monthly allowance of AI credits per seat (seats times the plan's credits). One credit is $0.01 of AI usage. Usage is tracked in real time and visible in Settings → Billing.

LLM Gateway

Velocity uses a provider-agnostic LLM gateway that supports multiple AI providers. The gateway automatically routes requests through available providers and handles failover if one is unavailable.

Supported Providers

Gateway Features

• Streaming responses — real-time token-by-token output with a typing cursor
• Concurrent stream limits — controlled per plan tier to prevent abuse
• Automatic retry — retries with exponential backoff on transient failures (429, 5xx)
• Provider fallback — if the primary provider fails, automatically tries the next
• Workspace overrides — workspaces can configure a preferred provider and model
• BYOK support — Enterprise workspaces can use their own API keys

Embedding Pipeline

Velocity generates vector embeddings for issues and documents to power semantic search. Embeddings use OpenAI’s text-embedding-3-small model (1536 dimensions) and are stored in PostgreSQL via the pgvector extension with HNSW indexing.

Embedding generation is fire-and-forget — when an issue or document is created or updated, an async request is dispatched to the embedding service. This means entity creation is never blocked by the embedding process. The embedding service deduplicates requests using content hashing to avoid unnecessary API calls.

Usage Tracking

Every AI API call is logged with:

• Feature name (search, triage, agent, embedding, etc.)
• Model and provider used
• Input and output token counts
• Cost in cents (calculated from per-model pricing)
• Duration in milliseconds
• User who triggered the request

Monthly aggregates are available via the aiUsage GraphQL query with per-feature breakdowns. The credit allowance is available via aiBudgetStatus.

Credit Allowance

When a workspace approaches its monthly AI credits:

• 80% used — a soft warning is shown to workspace admins
• 100% used — AI features are blocked until the allowance resets on the 1st (UTC), or the plan includes more credits

Workspace owners and admins can set a custom allowance with the setAiCreditOverride mutation.

Streaming & Concurrent Limits

AI features that use streaming (like the AI agent and description writer) deliver responses in real time with a typing cursor animation. Each user has a concurrent stream limit based on their workspace’s plan tier. If you exceed the limit, the request is rejected with a 429 status — wait for an existing stream to finish before starting a new one.

Feature Flag Overrides

Workspace administrators can override plan-tier AI access using feature flags. Feature flags use the ai:<feature_name> key convention (e.g., ai:ai_search) and can be managed in the admin dashboard under Feature Flags.