aimiles · MCP builder for publishers

Service status

Measured over the last 7 days — synthetic probes every 5 minutes plus every real request. Machine-readable at /api/status.

Service-level objectives

Availability (synthetic probes)target 99.9%measured 100%met
Search latency p95 (all real search calls)target < 300 msmeasured measuring
Error rate (all surfaces)target < 1%measured 48.15%missed

2013 probes since 2026-07-19 03:15 UTC · DB p50 30 ms · search-probe p95 114 ms

Per-surface traffic (7d)

SurfaceCallsErrorsp50p95p99
MCP (agents)00%0 ms0 ms0 ms
REST API00%0 ms0 ms0 ms
oasy landing (crawlers)2748.15%275 ms1827 ms2168 ms

How this platform scales

  • Autoscaling serverless compute (Vercel), pinned to cdg1 (Paris) — colocated with the database (AWS eu-west-3) so every query is a single-digit-millisecond hop.
  • Managed Postgres (Supabase) behind pgbouncer connection pooling; transaction pooler for request paths, session pooler for migrations.
  • Retrieval infrastructure operated for the publisher: chunking + embeddings written at ingest, HNSW vector index, hybrid semantic/full-text search with a latency budget and a two-tier query-embedding cache.
  • Model compatibility: every stored vector records its embedding model; search only compares vectors from the active model, so model upgrades re-embed incrementally with zero downtime — and content is consumable by any client over MCP, A2A, or plain REST.
  • Edge & token gateway: per-publisher rate limits, OAuth 2.1 bearer tokens hashed at rest, WAF/CDN redirect patterns for crawler traffic, custom-domain routing.