Diagram: five tinted data streams — call tracking, search & SEO, web analytics, CRM and email — curve inward from the edges of the frame, pass through a normalization ring, and leave the hub as a single canonical azure stream.
Call tracking {"caller":"+14155550142", "duration":214, "source":"gmb"} Search & SEO {"query":"pump repair", "clicks":38, "position":3.4} Web analytics {"session":"s_9f21", "engaged_s":96, "medium":"organic"} CRM {"deal":"d_4471", "value":4820, "stage":"quote"} Email {"campaign":"c_212", "opens":1840, "replies":37}All your tools. One flow.
APIfl0w connects the platforms you already use into one hub — one schema, one dashboard, one API. We build the connectors, we run the sync fabric, we own the breakage.
Call tracking Search & SEO Web analytics CRM Email
This is the product.
Every SaaS platform describes the same event a different way. A phone number is phone_number here, contactPhone there, dim_phone somewhere else — three formats, three field names, three ideas of what a duration means.
APIfl0w resolves that argument once, centrally, and keeps resolving it forever. Values land in a canonical record with full upstream lineage on every field. Fields we can't map are dropped loudly, never guessed at — you can read exactly what we discarded and why.
Many shapes in. One schema out.
This runs 3,300 times an hour across our fabric.
We build the connector if it has an API.
Categories, not logos. We operate connectors by capability — what a system yields into the hub — so swapping a vendor inside a category is a configuration change, not a migration.
We run it after we build it
A connector is not a deliverable. Auth expires, endpoints deprecate, rate limits change without notice. Every connector we build stays on our monitors with our pager attached to it.
New systems join the flow
Bring us a platform with a documented API and a credential we can scope down. Median time from stack walkthrough to first backfilled record in the hub is two weeks.
Vendor swaps stop being projects
Because records are canonical, replacing the CRM behind type=deal changes a connector config. Your dashboards, exports and API consumers never notice.
Connect. Normalize. Unify. Deliver.
Four stages, running continuously. Nothing here is a one-time migration — it is a service with a heartbeat.
CONNECT
We hold the credentials, poll the endpoints or receive the webhooks, honour every upstream rate limit, and backfill history on the way in. Retries use exponential backoff with jitter and a dead-letter queue you can inspect.
NORMALIZE
Each source field is mapped to a canonical field with an explicit type, unit and format. Phone numbers become E.164. Durations become seconds. Currency becomes minor units with an ISO code. Nothing is inferred silently.
UNIFY
Canonical records are deduplicated and merged on deterministic keys. Every field on a merged record carries lineage: which connector supplied it, at which sync, at which upstream timestamp.
DELIVER
One dashboard for the humans, one versioned REST API for the systems, and signed webhooks for anything that needs to react. Same records, same schema, three doors.
A regional industrial-equipment distributor
Eleven branches, a call-tracking platform for inbound service calls, an SEO suite for the parts catalogue, a web analytics property per region, and a CRM the outside sales team lived in. Four systems, four exports, four different opinions about what counted as a lead. Every Monday, six people rebuilt the same spreadsheet.
We built four operated connectors and backfilled twenty-six months of history. Calls, sessions, catalogue queries and deals now resolve into canonical lead and deal records keyed on phone number and branch. Attribution stopped being an argument because every field on every record says where it came from.
The Monday spreadsheet is gone. Branch managers open one dashboard; the ERP team reads the same numbers through GET /v1/records.
Fabric metrics
Canonical records written to the hub across every operated connector.
One completed sync run of one connector. The primary metered unit.
Upstream response to canonical record committed, p50 across the fabric.
The fabric, running.
Connectors pulse as their windows fire; packets ride the edges into the hub. Clients see their own version of this strip the moment they log in.
Figures shown are fabric-wide aggregates, refreshed continuously.
Walk us through your stack.
Tell us what you run and what you wish it told you. We will map it to the canonical schema on the call.