The confidence loop
EchoMode isn’t a tool. It’s a system that closes the loop around every agent.
01 · Build
For every agent you ship
Agent Builder
→
Define who the agent is — the baseline every turn is measured against.
Marketing
Legal
Support
Knowledge Base
→
Ground it in governed knowledge, imported from the storage you already use.
S3
Drive
Dropbox
OneDrive
Model hub · BYO inference
→
Your keys, your endpoints — any provider through one gateway.
OpenAI
Anthropic
Gemini
Llama
NVIDIA
02 · Control
For every turn in production
Runtime Control
→
Score the trajectory, catch drift early, counter-steer on the next turn.
Alignment
Turns 1–6
Control loop
Score → State → Steer
Fallback → kill
Kill Switch (Coming soon)
→
Fed by Runtime Control, every turn. When the state degrades past Fallback — or you say so — the switch trips.
MCP Tools
live
killed
03 · Prove
For every audit you’ll face
Logs & Observability
Watch the record live — session logs, per-turn traces, and alignment charts for every agent in production.
session logs
per-turn traces
alignment charts
latency
Audit Trail
→
Every turn, kill, and restore in one deterministic record — score, state, action, causal chain. Same input tomorrow, same record.
BigQuery
Snowflake
S3
Splunk
Datadog
CSV/JSON
Without EchoMode
Black-box AI — no view into why an agent answered the way it did.
High risk of drift, caught only after customers notice.
Slow, manual iteration on prompts nobody can review.
How it fits together
Every request crosses the same loop.
Your app calls one URL. Between the request and the response, EchoMode resolves the persona, gates retrieval by behavioral state, scores the turn, corrects drift, and writes the record.
Your app
→
Proxy API
→
Persona
→
Knowledge Base
→
Model
→
Score + FSM
→
Audit Trail
01 · Build
Stand agents up on your stack.
Agent Builder
Persona as a baseline, not a prompt.
A system prompt is a suggestion the model can ignore. In EchoMode the persona is the standard the agent is measured against — the reference for scoring, for state assignment, and for the audit trail. Define it once, without code.
→
Role, tone, constraints, scope — set conversationally
→
Embeddings, anchor words, and thresholds generated automatically
→
Versioned: diff behavior across versions, roll back regressions
→
Every conversation scores against its persona’s baseline
Go deeper on Agent Builder →
App
→
EchoMode
→
OpenAI / Anthropic / Meta
Proxy API
The whole platform is one line of config.
→
No SDK required — replace the base URL and ship
→
Multi-provider and LLM-agnostic, sub-100ms overhead
→
BYO inference: your keys, your endpoints, your data perimeter
→
Native TypeScript and Python SDKs when you want deeper hooks
Go deeper on Proxy API →
Knowledge Base
Retrieval that defends itself.
Standard RAG feeds whatever the conversation drifts toward. EchoMode binds each persona to a knowledge namespace and gates retrieval by behavioral state — a drifting agent loses access to the documents that would let it drift further.
→
Managed chunking, embedding, and indexing
→
Anchor words extracted automatically, tied to the persona baseline
→
State-aware gating: filtered at Mild, restricted at Moderate, suspended at Fallback
→
Citations captured on every retrieval
Go deeper on Knowledge Base →
Drive / S3 / SharePoint
→
EchoMode
→
BigQuery / Snowflake / SIEM
Connectors
Your stack, plugged into the control layer.
Documents come in from the storage you already use. Identity flows from your IdP. Inference routes to whichever provider you hold keys for. And the audit record streams out to the warehouse your analysts already query.
→
Document sources: S3, Google Drive, Dropbox, OneDrive, SharePoint
→
Model providers: OpenAI, Anthropic, Gemini, Meta, and more via one gateway
→
Identity: OAuth, SSO, SAML — RBAC inherits from the caller
→
Exports: BigQuery, Snowflake, S3, SIEM
Go deeper on Connectors →
02 · Control
Govern behavior while it runs.
Runtime Control
Drift is caught and corrected on the next turn, before it compounds.
Guardrails check one output and move on. EchoMode scores the whole trajectory — every turn, against the persona baseline — smooths it with EWMA, assigns a behavioral state, and counter-steers the moment the trend degrades.
→
Deterministic 0–100 alignment score on every turn
→
Four-state FSM: Stable, Mild, Moderate, Fallback
→
BFS anchor injection pulls the model back on persona
→
Hard enforcement at Fallback — the model can’t bypass it
Go deeper on Runtime Control →
Alignment across 7 turns
Turns 1–7
Stable
Stable
Mild
Moderate
Fallback
Moderate
Stable
Runtime targets
prod · us-east
Agent
support-bot
persona@v3.2 · 1.2k sessions/day
live
Key
em_prod_8f31…
killed 14:02 UTC · by s.chen · reason: leaked key
killed
Kill Switch
When an agent has to stop, it stops. Now.
Behavioral correction handles drift. The kill switch handles everything else: a compromised key, a bad deploy, a tenant that needs freezing. One action at the proxy layer halts traffic instantly — scoped as narrowly or broadly as you need.
→
Kill by agent, API key, team, tenant, or the whole org
→
Enforced at the proxy — no client redeploy, nothing to flush
→
Every kill and restore lands in the audit trail with actor and reason
→
Staged degradation first: Fallback state before full stop
Go deeper on Kill Switch →
03 · Prove
Show your work, on demand.
Audit Trail
Proof, not probability.
LLM-as-judge gives you a second opinion from the same kind of system that produced the failure. EchoMode writes a deterministic record instead: fixed scoring function, fixed FSM, full causal chain. Same input tomorrow, same record.
→
Per-turn capture: input, output, score, state, action, latency
→
Causal chain — which anchors fired, which documents were filtered, why
→
Replay any session and diff across persona versions
→
Export to CSV, JSON, your warehouse, or your SIEM
Go deeper on Audit Trail →
Turn 143
·
Score 88
·
Stable
·
—
Turn 144
·
Score 62
·
Moderate
·
L0 anchor inject
Turn 145
·
Score 78
·
Mild
·
recover
Causal chain preserved: L0 anchors [scope, persona, refusal-policy] · retrieval filtered (3 docs)
See the whole loop on your own traffic.
Connect in an afternoon. Govern in real time. Prove it after.
© 2026 echomode.io