THE ENGINE

One engine.
Any environment.

Community, audience, dataset, review corpus — it reads the environment first, then produces the intelligence the data actually warrants. Not the same template for everything.

7+
Environments read
Adaptive
Output shapes
5
Agents on top
HOW IT READS

From interaction
to verdict.

Same architecture, every analysis. What changes is what the data warrants saying.

01 — Interactions characterized in context
02 — Patterns across actors over time
03 — The environment understood as a whole
01

Every interaction analyzed in context.

The engine doesn't read messages. It reads what messages do — to the conversation, to the relationship between participants, to the environment as a whole.

{ actor: "a8f3c1d", analyzed: true, timestamp: "2026-04-03T14:22:11Z" }
02

Behavior over time builds a profile. Profiles reveal what's coming.

In environments where the same actors return, the engine tracks consistency, trajectory, and triggers across weeks of interaction. Not what someone said — what they've been doing.

Sam Chen ─────────────────────────────────── role: stabilizer status: departure risk emerging also: bridges two sub-groups trend: declining ↓ 14 days driven by: low acknowledgment
03

The full picture. What's happening, where it's going, what to do.

The engine synthesizes everything it's learned into the most useful form of intelligence the data supports. Not a dashboard. A verdict — with reasoning attached.

health: 61 ↓ from 74 drift: culture fragmenting alert: anchor may step back forecast: "Engagement drops 23% if Sam reduces activity" confidence: high within: 14 days
ENVIRONMENTAL ASSESSMENT

The engine reads the room before it reads the data.

Most systems apply the same framework to every dataset. BIE characterizes the environment first — then decides what intelligence is worth producing.

assessment.run
ASSESSING ENVIRONMENT...
› Reading interaction structure...
› Characterizing environment...
› Determining relevant frameworks...
──────────────────────────────────────────────────
ENVIRONMENT CLASSIFIED: community
BEHAVIORAL FRAMEWORK: full_profile
OUTPUT MODE: full behavioral profile
_
COMMUNITY OUTPUT
·Behavioral archetypes
·Dependency risk mapping
·Drift detection
·Early warnings
·Falsifiable predictions
REVIEW DATASET OUTPUT
·Operational signal extraction
·Sentiment trajectory
·Problem concentration map
·Impact attribution
·Pre-rating early warnings
// same engine · environment determines output
BEHAVIORAL SIGNALS

Five dimensions. Every interaction.

The engine doesn't count messages. It characterizes what each interaction did.

signal_categorytype
Conversational dynamics
Influence patterns
Actor relationship mapping
Behavioral trajectory
Risk indicators
Sentiment direction
Engagement quality
Participation consistency

Behavioral signals

The engine extracts signals from each interaction as a unit within its context — not just content analysis, but what the interaction did to the conversation and the actors in it.

ADAPTIVE OUTPUT

Same engine.
Output adapts to what the data warrants.

Send interaction data. The engine characterizes the environment. Intelligence adapts.

// POST /api/v1/ingest · same endpoint · different intelligence
Weekly Intelligence Report
61
HEALTH

This community is fragmenting at the leadership layer. Sam Chen has been the primary cohesion actor for 22 weeks — their response time has dropped 40% over the past 14 days and their longest-running threads have gone quiet.

Three members joined in the same week Sam's engagement began declining. This timing suggests the community's gravitational center is shifting rather than simply weakening.

EARLY WARNING
flag: anchor may step back
person: Sam Chen
signal: 14-day pattern match
risk: HIGH
PREDICTION
"Engagement drops 23% if Sam
reduces activity in next 14 days"
confidence: 0.74
RECOMMENDED ACTION
Reach out to Sam this week.
Cyrano has a draft ready.
AGENTIC INTELLIGENCE

Intelligence doesn't wait for the weekly report.

Six agents receive intelligence and act on it. Each has a name because the messages should feel like they came from a person.

Argus

The Scout

Scans the environment constantly. Surfaces signals before they reach the weekly report.

From: Argus3 hours ago

Sam's response times dropped 40% this week. Three of their longest-running threads have gone quiet — threads where they were the primary responder for weeks.

This matches the behavioral pattern I've tracked in two previous communities, 12–16 days before a key member reduced activity significantly.

Flagging now. If this continues through the weekend, Minerva should factor it into this week's plan.

You can reply to this · Thread depth 1/5
THREE WAYS IN

Infrastructure, not a feature.

BIE is built to be embedded in other things, not just used as a product.

BEHAVIORAL INTELLIGENCE API

Any developer, any platform. Send interaction data in the standard schema. Receive behavioral intelligence back. No connector required.

curl -X POST https://api.bieintel.com/v1/ingest \
  -H "Authorization: Bearer $BIE_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "actor":     "user_a8f3c1",
    "content":   "...",
    "timestamp": "2026-04-03T14:22:11Z",
    "source":    "your_platform"
  }'

// → 200 OK
{
  "session_id": "ses_019f3a...",
  "status":     "processing",
  "webhook":    "POST /your-endpoint when ready"
}
GET /api/v1/intelligence/:session_id · POST webhook on completion
PLATFORM CONNECTORS

Discord · YouTube · Instagram · Slack · Teams. Connect via OAuth. Intelligence begins immediately.

DiscordYouTubeInstagramSlackTeams
BULK / RESEARCH MODE

Upload existing datasets. Specify what you're trying to understand. The engine characterizes the environment and returns intelligence appropriate to the data.

CSV · JSON · raw export · any format
GET STARTED

You've seen how it works.

Pick the path that fits.

// bieintel.com · behavioral intelligence infrastructure