User Profile

Overview

The User Profile is a structured document Synap maintains for every end user of your instance: a set of critical attributes you define (typed fields like a customer’s budget, preferred language, or purchase timeline), a short narrative overview, and an extras bucket for stable facts that fall outside your schema. Profiles are built exclusively from what users actually said in ingested conversations, extracted, never inferred. If a conversation never touched an attribute, that attribute stays blank. Every populated attribute carries its own confidence, timestamp, and the ID of the conversation it came from. The profile is designed for conversation-start injection: one low-latency fetch returns the profile (plus recent conversation summaries) ready to paste into your agent’s system prompt; see Context Fetch and user.get_profile.

Availability and enabling

The feature ships platform-wide and is on by default for every instance, and its model call is included in that document’s ingestion charge. Without any configuration, Synap maintains the narrative overview and the extras bucket for each user. To get the full value, define your critical attributes in the instance’s configuration: contact your Maximem team or use your dashboard’s instance configuration.

Turning it off applies to future ingestions only. The setting is read when a document is ingested, so switching it on does not backfill profiles from documents already processed, and switching it off leaves existing profiles in place. Either way, the next ingestion is the first one affected.The setting is per instance, not per account: each instance carries its own user_profile block, so one instance can run profiles while another does not.

An instance can opt out entirely by setting enabled: false; that choice is preserved across configuration regenerations.

{
  "user_profile": {
    "enabled": true,
    "overview_enabled": true,
    "max_profile_tokens": 1000,
    "critical_attributes": [ ... ]
  }
}

Your attribute definitions are treated as client-owned state: they survive memory-architecture regeneration and instance promotion unchanged.

Defining critical attributes

Each attribute is a typed field:

Field	Type	Notes
`name`	string	snake_case identifier, e.g. `budget_range`
`type`	`string` \| `number` \| `boolean` \| `enum` \| `list`	`enum` requires `allowed_values`
`description`	string	Guides extraction: state exactly what qualifies
`allowed_values`	string[]	Closed set for `enum` types
`required`	boolean	Flags the attribute as expected (used by dashboards; extraction still never invents a value)
`examples`	string[]	Optional hints for open-ended fields

A realistic schema for a sales assistant:

"critical_attributes": [
  {"name": "customer_name", "type": "string",
   "description": "Only if explicitly stated by the customer, never inferred. Preferred name."},
  {"name": "preferred_language", "type": "string",
   "description": "Preferred conversation language.", "examples": ["English", "Hindi"]},
  {"name": "product_interest", "type": "enum",
   "description": "Product line the customer asked about.",
   "allowed_values": ["Starter", "Professional", "Enterprise"]},
  {"name": "budget_range", "type": "string",
   "description": "Budget exactly as stated by the customer."},
  {"name": "decision_timeline", "type": "enum",
   "description": "Stated purchase timeline.",
   "allowed_values": ["Immediate", "3 months", "6+ months"]},
  {"name": "main_objection", "type": "string",
   "description": "Biggest objection raised.", "examples": ["Price", "Integration effort"]}
]

Write descriptions as extraction instructions. A phrase like “only if explicitly stated by the customer” in the description is honored by the extraction pass: fields stay blank until a conversation genuinely provides the value.

How the profile is built

The profile updates as a by-product of normal ingestion; there is no separate API call to maintain it:

Your application pushes a conversation (for example with conversation.ingest_transcript) and moves on; everything below is asynchronous and off your hot path.
Synap’s ingestion pipeline extracts long-term memories from the transcript.
At the end of the pipeline, the profile step loads your instance’s attribute schema and merges newly extracted, conversation-grounded values into the user’s profile document, updating only attributes the conversation actually evidenced, respecting allowed_values, and rewriting the narrative overview.
Each write bumps the profile’s version and records, per attribute, the source conversation ID and timestamp. Unrelated attributes are never touched, and concurrent ingestions for the same user merge safely.

Stable facts that don’t match any configured attribute are kept in the profile’s extras object rather than discarded. Client-supplied analysis passed with the transcript is used as extraction hints only; the transcript remains the source of truth.

Attribute-schema edits take effect on new ingestions within a few minutes (configuration is cached briefly). Existing profile values are preserved; new and changed attributes populate as subsequent conversations provide evidence.

Reading the profile

At conversation start, fetch the profile together with recent conversation summaries in one call:

ctx = await sdk.fetch(
    user_id="user-123",
    context_mode="conversation-summary",
    include_profile=True,
    last_n_conversations=1,
)
prompt_block = ctx.formatted_context   # "## Caller Profile" + "## Previous Conversations"
profile = ctx.profile                  # typed document, or None if not yet built

const ctx = await sdk.fetch({
  user_id: 'user-123',
  context_mode: 'conversation-summary',
  include_profile: true,
  last_n_conversations: 1,
});
const prompt_block = ctx.formatted_context;  // "## Caller Profile" + "## Previous Conversations"
const profile = ctx.profile;  // typed document, or None if not yet built

const ctx = await sdk.fetch({
  user_id: 'user-123',
  context_mode: 'conversation-summary',
  include_profile: true,
  last_n_conversations: 1,
});
const prompt_block = ctx.formatted_context;  // "## Caller Profile" + "## Previous Conversations"
const profile = ctx.profile;  // typed document, or None if not yet built

Or read it directly:

profile = await sdk.user.get_profile(user_id="user-123")

const profile = await sdk.user.get_profile({
  user_id: 'user-123',
});

const profile = await sdk.user.get_profile({
  user_id: 'user-123',
});

The document shape:

{
  "attributes": {
    "budget_range": {
      "value": "about 20k per year",
      "confidence": 1.0,
      "updated_at": "2026-08-01T10:14:03Z",
      "source_conversation_id": "call-0042"
    }
  },
  "overview": "Short narrative summary of who this user is and what they want.",
  "extras": {"team_size": 40},
  "_meta": {"schema": 1, "version": 3, "updated_at": "2026-08-01T10:14:03Z"}
}

See user.get_profile for response details and Response Shapes for the typed models.

Set up Synap Cloud

What to capture

SDK lifecycle

Memory operations

Responses and errors

Scoping and data

Operate

Overview

Availability and enabling

Defining critical attributes

How the profile is built

Reading the profile

​Overview

​Availability and enabling

​Defining critical attributes

​How the profile is built

​Reading the profile

Overview

Availability and enabling

Defining critical attributes

How the profile is built

Reading the profile