Discovery & Intelligence

`GET` `/api/discover`

Filter locations by score thresholds across all metros. Query parameters

Name	Type	Default	Description
`metro`	string		Metro slug filter.
`compositeMin`	int		Minimum composite score.
`businessMin`	int		Minimum Business Vitality.
`safetyMin`	int		Minimum Safety score.
`limit`	int	`50`	Max results.

Example

curl "https://axiomlocus.io/api/discover?metro=sf&compositeMin=60&safetyMin=50"

Response

{ "total": 12, "results": [{ "h3_index": "...", "metro_slug": "sf", "location_name": "Mission District", "composite": 74 }] }

Field	Type	Description
`total`	number	Number of matching locations
`results[].composite`	number	Composite score 0-100
`results[].location_name`	string	Neighborhood name

`GET` `/api/nearby`

Everything we know near a location — permits, POIs, schools, clinical trials, FDA events, zoning. Query parameters

Name	Type	Required	Default	Description
`lat`	float	✓		Latitude.
`lng`	float	✓		Longitude.

Example

curl "https://axiomlocus.io/api/nearby?lat=37.7749&lng=-122.4194"

Response

{ "summary": { "permits": 45, "pois": 120, "schools": 3, "clinical_trials": 8 }, "recent": { ... } }

Field	Type	Description
`summary`	object	Count of records per data type within ~1km
`recent`	object	Recent records from each data type

`GET` `/api/metro-tier-distribution`

Count of scored cells in each safety tier bucket for a given signal across a metro. Powers the tier-mix bar on the Explorer Intelligence Rail so you can see at a glance whether a metro is mostly safe or mostly elevated, without leaving the page. Buckets follow the standard composite score breakpoints: Prime ≥80, Strong 60–79, Solid 40–59, Watch 20–39, Elevated <20. Cells with a null value for the requested signal are excluded. Query parameters

Name	Type	Required	Default	Description
`metro`	string	✓		Metro slug (e.g. `sf`, `nyc`, `denver`).
`signal`	string		`safety_environment`	Column to bucket on. One of `composite`, `business_vitality`, `population_momentum`, `demographics`, `economic_strength`, `development_pipeline`, `accessibility`, `safety_environment`, `amenity_demand`.

Example

curl "https://axiomlocus.io/api/metro-tier-distribution?metro=sf&signal=safety_environment"

Response

{
  "metro": "sf",
  "signal": "safety_environment",
  "total": 1284,
  "buckets": {
    "prime": 412,
    "strong": 537,
    "solid": 246,
    "watch": 71,
    "elevated": 18
  }
}

Field	Type	Description
`metro`	string	Metro slug echoed from the request.
`signal`	string	Signal column the distribution is computed over.
`total`	number	Total scored cells included in the distribution (cells with `null` on the requested signal are excluded).
`buckets.prime`	number	Cells scoring ≥ 80.
`buckets.strong`	number	Cells scoring 60–79.
`buckets.solid`	number	Cells scoring 40–59.
`buckets.watch`	number	Cells scoring 20–39.
`buckets.elevated`	number	Cells scoring < 20.

The same endpoint backs distribution bars for any signal group — pass a different signal to render a development-pipeline mix, business-vitality mix, or composite mix without a separate route.

`GET` `/api/score-trends`

Historical score trends for a metro or specific H3 cell. Pass metro for a metro-wide aggregate trend or h3_index for a per-cell time-series with all eight signal-group sub-scores. Exactly one of the two is required. The endpoint reads from the score_history table that the Railway scorer snapshots once per day, so a fresh row appears for every (h3_index, profile, snapshot_date) covered by that day’s scorer pass. Cells the scorer didn’t touch on a given day will be absent from the time-series for that date. Query parameters

Name	Type	Default	Description
`metro`	string		Metro slug for an aggregate metro-wide trend.
`h3_index`	string		Specific H3 cell for a detailed per-cell trend with signal-group breakdowns.
`days`	int	`90`	Lookback period in days.

Metro aggregate example

curl "https://axiomlocus.io/api/score-trends?metro=sf&days=30"

{ "metro": "sf", "days": 30, "trend": [{ "date": "2026-03-30", "avg_composite": 42, "cells": 20 }] }

Field	Type	Description
`trend[].date`	string	Snapshot date (`YYYY-MM-DD`)
`trend[].avg_composite`	number	Average composite score across the metro for that date
`trend[].cells`	number	Cells in the metro with a snapshot on that date

Per-cell example

curl "https://axiomlocus.io/api/score-trends?h3_index=882a1072d3fffff&days=90"

{
  "h3_index": "882a1072d3fffff",
  "days": 90,
  "snapshots": [
    {
      "snapshot_date": "2026-04-29",
      "composite": 71,
      "business_vitality": 68,
      "population_momentum": 74,
      "demographics": 65,
      "economic_strength": 80,
      "development_pipeline": 77,
      "accessibility": 62,
      "safety_environment": 70,
      "amenity_demand": 64
    }
  ]
}

Field	Type	Description
`snapshots[].snapshot_date`	string	Snapshot date (`YYYY-MM-DD`)
`snapshots[].composite`	number	Cell composite score 0–100 on that date
`snapshots[].business_vitality` … `snapshots[].amenity_demand`	number \| null	Per-group sub-score 0–100; `null` if the group could not be computed for that snapshot

`GET` `/api/top-movers`

Discover the cells whose composite score has changed the most over a 7-, 30-, 90-, or 180-day window. Each row reports the latest composite, the prior-window composite, and the delta between them, so you can surface neighborhoods that are heating up (or cooling off) without manually diffing snapshots from /api/score-trends. Deltas are computed against the freshest snapshot in score_history at or before the lookback boundary, not a fixed calendar date. This means partial scorer coverage on any given day does not bias the leaderboard — cells without a baseline snapshot inside the window are simply excluded. The same RPC powers the metro-overview “movement” rail in the Explorer and the standalone /movers page in the dashboard. Query parameters

Name	Type	Default	Description
`days`	int	`30`	Lookback window. Must be one of `7`, `30`, `90`, or `180`.
`direction`	string	`up`	`up` for biggest gainers, `down` for biggest decliners, or `all` to rank by absolute delta.
`metro`	string		Metro slug filter (e.g. `sf`, `nyc`, `boston`). Omit for cross-metro results.
`limit`	int	`25`	Max results (1–100).

Example

curl "https://axiomlocus.io/api/top-movers?days=30&direction=up&metro=boston&limit=10"

Response

{
  "window_days": 30,
  "direction": "up",
  "metro": "boston",
  "movers": [
    {
      "h3_index": "882a306665fffff",
      "metro_slug": "boston",
      "location_name": "Seaport District",
      "latest_composite": 61,
      "prior_composite": 38,
      "delta": 23,
      "latest_snapshot_date": "2026-04-29",
      "prior_snapshot_date": "2026-03-30"
    }
  ]
}

Field	Type	Description
`window_days`	int	Lookback window echoed from the request.
`direction`	string	`up`, `down`, or `all` — echoed from the request.
`metro`	string \| null	Metro slug filter, or `null` when the call was cross-metro.
`movers`	array	Cells ranked by composite delta. Empty when the window has no eligible snapshot pairs yet.
`movers[].h3_index`	string	H3 cell index.
`movers[].metro_slug`	string	Metro the cell belongs to.
`movers[].location_name`	string	Neighborhood name.
`movers[].latest_composite`	number	Composite score 0–100 from the most recent snapshot.
`movers[].prior_composite`	number	Composite score 0–100 from the freshest snapshot at or before the lookback boundary.
`movers[].delta`	number	`latest_composite - prior_composite`. Positive when the cell is improving, negative when declining.
`movers[].latest_snapshot_date`	string	Date of the latest snapshot (`YYYY-MM-DD`).
`movers[].prior_snapshot_date`	string	Date of the prior-side snapshot used as the baseline.

Daily snapshots accumulate from the moment a cell is first scored, so newer metros may return an empty movers array on longer windows until enough history has built up. Use a shorter window (days=7) to surface activity earlier.

`GET` `/api/schools`

Nearby school quality ratings (1-10 scale). Query parameters

Name	Type	Required	Default	Description
`lat`	float	✓		Latitude.
`lng`	float	✓		Longitude.
`radius`	float		`2`	Radius in miles.
`limit`	int		`10`	Max results.

Example

curl "https://axiomlocus.io/api/schools?lat=37.7749&lng=-122.4194&radius=1"

Response

{ "total": 5, "schools": [{ "name": "Lincoln Elementary", "rating": 8, "enrollment": 450 }] }

Field	Type	Description
`schools[].rating`	number	Quality score 1-10
`schools[].enrollment`	number	Student enrollment

`GET` `/api/life-sciences`

Clinical trials and FDA enforcement data by state or sponsor. Query parameters

Name	Type	Default	Description
`state`	string		US state name.
`sponsor`	string		Sponsor name (partial match).
`type`	string	`all`	Filter: trials, fda, or all.
`limit`	int	`50`	Max results.

Example

curl "https://axiomlocus.io/api/life-sciences?state=Massachusetts&type=trials&limit=10"

Response

{ "trials": { "total": 10, "data": [{ "nct_id": "NCT05754281", "sponsor": "Joslin Diabetes Center" }] } }

Field	Type	Description
`trials.data[].nct_id`	string	ClinicalTrials.gov trial ID
`trials.data[].sponsor`	string	Lead sponsor organization

`GET` `/api/zoning`

Zoning district rules — allowed uses, height limits, FAR, setbacks. Query parameters

Name	Type	Required	Description
`metro`	string	✓	Metro slug.
`code`	string		Specific district code.
`category`	string		Filter: residential, commercial, industrial, mixed_use.

Example

curl "https://axiomlocus.io/api/zoning?metro=denver&category=commercial"

Response

{ "metro": "denver", "total": 8, "districts": [{ "district_code": "C-MX-5", "max_height_ft": 65, "max_far": 3.0 }] }

Field	Type	Description
`districts[].district_code`	string	Zoning designation code
`districts[].max_height_ft`	number	Maximum building height in feet
`districts[].max_far`	number	Floor area ratio

`GET` `/api/port-risk`

Surface upstream port disruption affecting a Locus metro’s economic catchment. Twenty-two metros are mapped to their primary and secondary ports by trucking corridor (e.g. phoenix → Long Beach via I-10, atlanta → Savannah via I-16). When an inbound port shows elevated wait times in Overwatch, the row appears here with a risk_level of watch, elevated, or severe, derived from p90 wait, median wait, and trend direction. Returns an empty risks array when no upstream port is currently disrupted — the PortRiskBadge on cell-detail panels uses that signal to hide itself. Use this to flag CRE locations whose tenants depend on container imports (industrial, logistics, big-box retail) before a soft port closure shows up in occupancy or rent comps. Query parameters

Name	Type	Required	Default	Description
`metro`	string	✓		Metro slug (e.g. `houston`, `atlanta`, `chicago`).

Example

curl "https://axiomlocus.io/api/port-risk?metro=atlanta"

Response

{
  "metro": "atlanta",
  "risks": [
    {
      "port_slug": "savannah",
      "port_name": "Port of Savannah",
      "tier": "primary",
      "trucking_km": 400,
      "median_wait_hours": 18,
      "p90_wait_hours": 84,
      "vessel_count": 23,
      "trend_direction": "worsening",
      "trend_consecutive_periods": 3,
      "risk_level": "severe",
      "measured_at": "2026-04-29T00:00:00Z"
    }
  ]
}

Field	Type	Description
`metro`	string	Metro slug echoed from the request.
`risks`	array	Active port-risk rows, ordered by `risk_level` then `p90_wait_hours` (highest first). Empty when no upstream port is disrupted.
`risks[].port_slug`	string	Stable port identifier (e.g. `savannah`, `long-beach`, `ny-nj`).
`risks[].port_name`	string	Human-readable port name.
`risks[].tier`	string	`primary` or `secondary` — the port’s role in the metro’s catchment.
`risks[].trucking_km`	number	Driving distance from port to metro centroid (km).
`risks[].median_wait_hours`	number	Median vessel wait time at the port over the measurement window.
`risks[].p90_wait_hours`	number	90th-percentile wait — the figure that drives most risk-level transitions.
`risks[].vessel_count`	number	Vessels currently queued or anchored upstream.
`risks[].trend_direction`	string	`worsening`, `stable`, or `improving`.
`risks[].trend_consecutive_periods`	number	Periods the trend has held — used to confirm sustained disruption vs. a single-day spike.
`risks[].risk_level`	string	`watch`, `elevated`, or `severe`.
`risks[].measured_at`	string	ISO 8601 timestamp of the underlying Overwatch measurement.

`GET` `/api/export`

Requires Bearer token.

Export scored location data as CSV or JSON. Requires Pro or Team plan (bulk_export entitlement). Query parameters

Name	Type	Default	Description
`metro`	string		Metro slug filter (e.g. `sf`, `nyc`).
`format`	string	`csv`	`csv` or `json`.
`saved`	boolean	`false`	When `true`, restricts the export to the caller’s saved cells (the cells in their `monitored_locations` portfolio). Composes with `metro`.
`limit`	int	`1000`	Max rows (5000 max).

Portfolio export (saved=true) Set saved=true to export only the cells the authenticated user has saved into their portfolio (their monitored_locations). This is the intended workflow for analysts who track a curated set of cells across metros and want a CSV/JSON snapshot of just those rows rather than a full-metro or platform-wide pull.

The filter is applied as an IN over the caller’s saved h3_index list, so the result respects ordering by composite (descending) and the limit cap.
It composes with metro — combining saved=true&metro=sf returns only saved cells inside SF.
If the user has no saved cells, the endpoint short-circuits to an empty payload (200 OK) without scanning cell_scores. CSV responses return an empty body; JSON responses return { "total": 0, "data": [] }.
The download filename is tagged saved (e.g. axiom-locus-saved-2026-04-29.csv) instead of the metro slug or all, so portfolio exports are easy to identify on disk.

Examples Export all SF cells as CSV:

curl "https://axiomlocus.io/api/export?metro=sf&format=csv" -H "X-API-Key: al_xxx"

Export the caller’s saved cells (portfolio) as CSV:

curl "https://axiomlocus.io/api/export?saved=true&format=csv" -H "X-API-Key: al_xxx"

Export the caller’s saved cells inside one metro as JSON:

curl "https://axiomlocus.io/api/export?saved=true&metro=sf&format=json" -H "X-API-Key: al_xxx"

Response

h3_index,metro_slug,location_name,composite,...
88283082e7fffff,sf,Mission District,74,...

`GET` `/api/bids`

Search federal and government procurement opportunities sourced from SAM.gov. Filter by state, keyword, or NAICS code to find relevant contracts. Query parameters

Name	Type	Default	Description
`state`	string		Two-letter state code (e.g. `TX`, `CA`).
`keyword`	string		Full-text search across title and description.
`naics`	string		NAICS code filter (e.g. `236220` for commercial construction).
`type`	string		Bid type (partial match).
`active`	string	`true`	Set to `false` to include expired bids.
`limit`	int	`50`	Max results (max 200).

Example

curl "https://axiomlocus.io/api/bids?state=TX&keyword=construction&limit=10"

Response

{
  "state": "TX",
  "keyword": "construction",
  "count": 10,
  "bids": [
    {
      "notice_id": "SAM-2026-001234",
      "title": "Renovation of Federal Building, Houston TX",
      "type": "Solicitation",
      "agency": "General Services Administration",
      "posted_date": "2026-04-10",
      "response_deadline": "2026-05-15",
      "description": "Full interior renovation of the federal courthouse...",
      "naics_code": "236220",
      "place_of_performance_city": "Houston",
      "place_of_performance_state": "TX",
      "estimated_value": 4500000,
      "url": "https://sam.gov/opp/abc123",
      "set_aside_type": "Small Business"
    }
  ]
}

Field	Type	Description
`count`	int	Number of matching bids returned.
`bids[].notice_id`	string	SAM.gov notice identifier.
`bids[].response_deadline`	string	Deadline for bid submissions.
`bids[].naics_code`	string	NAICS industry classification code.
`bids[].estimated_value`	number	Estimated contract value in USD.
`bids[].set_aside_type`	string	Set-aside designation (e.g. `Small Business`, `8(a)`, `HUBZone`).

​GET /api/discover

​GET /api/nearby

​GET /api/metro-tier-distribution

​GET /api/score-trends

​GET /api/top-movers

​GET /api/schools

​GET /api/life-sciences

​GET /api/zoning

​GET /api/port-risk

​GET /api/export

​GET /api/bids

`GET` `/api/discover`

`GET` `/api/nearby`

`GET` `/api/metro-tier-distribution`

`GET` `/api/score-trends`

`GET` `/api/top-movers`

`GET` `/api/schools`

`GET` `/api/life-sciences`

`GET` `/api/zoning`

`GET` `/api/port-risk`

`GET` `/api/export`

`GET` `/api/bids`