# convrgent.ai — Relationship Evolution Analysis

> convrgent.ai — Relationship Evolution Analysis is a paid API for AI agents from convrgent.ai, paid per call via x402, $3/call, status unknown (last checked 2026-09-15).

Analyzes how a relationship has changed over time, identifying trust trajectory, inflection points, and patterns like honeymoon fade, slow build, or rupture-repair cycles.

## Facts

- Endpoint: POST https://convrgent.ai/api/kyh/multi/evolution
- Price: $3/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/convrgent-ai-130a68bf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_41RFqJESVXtujjhl9ctnX

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability convrgent-ai-130a68bf -d '<json body>'
```

Example prompt: Look at the last 8 months of my conversations with Jordan and tell me how our relationship has evolved — I want to know the trust trajectory, any major turning points, whether we went through a rupture-repair cycle, and where things seem to be heading.

## When to prefer this

Use this endpoint when you need to understand how a relationship has changed over time rather than just its current state. Unlike the real-time health scoring endpoint (which gives a snapshot), this endpoint performs longitudinal analysis across multiple time periods to surface trends, inflection points, and predictive trajectory. Ideal for detecting drift, reconciliation events, or relationship phase transitions.

## Known failure modes

- Insufficient conversation history — too few messages to establish temporal patterns
- Missing time metadata on messages — cannot perform temporal analysis without timestamps
- Single data point only — evolution analysis requires at least two time periods
- Ambiguous participant identity — multi-party conversations confuse two-person relationship mapping
- Malformed input payload — incorrect schema for conversation history entries

## How this service works

Relationship evolution — how a relationship changed over time. Trust trajectory, temporal analysis, inflection points, pattern recognition (honeymoon fade, slow build, rupture repair), relationship health tracking, trend forecasting.

## Output

Returns a temporal relationship analysis including a trust trajectory curve, identified inflection points with timestamps, pattern labels (e.g. honeymoon fade, slow build, rupture-repair), an overall relationship health trend, and a short forecast of where the relationship is headed based on observed patterns.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "bodyType",
    "body",
    "method"
   ],
   "properties": {
    "body": {
     "required": [
      "human_a",
      "human_b",
      "snapshots"
     ],
     "properties": {
      "context": {
       "type": "object"
      },
      "human_a": {
       "type": "object",
       "properties": {
        "birthData": {
         "type": "object",
         "required": [
          "year",
          "month",
          "day",
          "location"
         ],
         "properties": {
          "day": {
           "type": "integer"
          },
          "hour": {
           "type": "integer",
           "description": "Highly recommended. Defaults to 12 if omitted."
          },
          "year": {
           "type": "integer"
          },
          "month": {
           "type": "integer"
          },
          "minute": {
           "type": "integer",
           "description": "Defaults to 0 if omitted."
          },
          "latitude": {
           "type": "number",
           "description": "Optional override"
          },
          "location": {
           "type": "string",
           "description": "City and country. Coordinates auto-resolved."
          },
          "timezone": {
           "type": "number",
           "description": "Optional — auto-resolved from location"
          },
          "longitude": {
           "type": "number",
           "description": "Optional override"
          }
         }
        },
        "responses": {
         "type": "object"
        },
        "textSamples": {
         "type": "array",
         "items": {
          "type": "object",
          "required": [
           "text"
          ],
          "properties": {
           "text": {
            "type": "string"
           },
           "context": {
            "type": "string"
           }
          }
         }
        },
        "observations": {
         "type": "object"
        }
       }
      },
      "human_b": {
       "type": "object",
       "properties": {
        "birthData": {
         "type": "object",
         "required": [
          "year",
          "month",
          "day",
          "location"
         ],
         "properties": {
          "day": {
           "type": "integer"
          },
          "hour": {
           "type": "integer",
           "descri
… (truncated)
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "trend": "positive-growth",
  "pattern": "slow-build",
  "timespan": "4 months",
  "current_state": {
   "trust": 70,
   "trajectory": "ascending"
  },
  "inflection_points": [
   {
    "event": "...",
    "timestamp": "..."
   }
  ],
  "agent_recommendation": "..."
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/convrgent-ai-130a68bf/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from convrgent.ai](https://www.zero.xyz/host/convrgent.ai/llms.txt)