AI agentsyourrules
Run agents, multi-model decision paths, and security oversight—on one platform.
Production agentic AI, unified under one control plane
Alongside the Agentic AI lifecycle, secure chat, SDK gateway, conversational AI operations, security infrastructure, and observability services run together inside the same tenant.
Three operating layers
Workflow · debate · eval
9-step turn pipeline
45 modules · 6 groups
Pipeline · template · session
Policy · approval · quarantine
PII · egress · RAG guard
Audit chain · SLO · KPI
Webhook · MCP · connector
Agent Design and Versioning
Prepare production-ready agents inside Misel.
Define agent identity, versions, prompts, tool permissions, and knowledge sources in one system. Knowledge Pool and Connect connectors attach to the same tenant knowledge and integration layer.
Versioned agent definition
Agent identity, behavioral contract, and operating scope are version-controlled with full change traceability.
Prompt and model configuration
System/developer prompts and model parameters are managed as release artifacts, with safe rollback paths.
Tool and knowledge integration
Connectors, tool permissions, and RAG sources are bound per agent with clear access boundaries.
Pre-production flow readiness
Workflows, intents, and trigger logic are validated before go-live to reduce runtime uncertainty.
Execution and Decision Orchestration
Run agents with optional multi-agent deliberation.
Operate sync, background, and persistent run modes. Secure Chat and Conversational AI are separate consumption surfaces that reuse the same security and policy layer.
Multi-mode execution control
Operate the same agent flow in sync, background, or persistent modes based on operational demand.
Multi-agent deliberation
For high-impact decisions, multiple agents evaluate the same context to reduce single-model bias.
Thresholds with human fallback
When confidence or consensus thresholds are not met, decisions are routed into human approval paths automatically.
Live trace and replayability
Run events, decision steps, and outcomes are observable in real time and analyzable post-run via replay.
Governance, Approval, and Live Operations
Scale in production without losing control.
Policies, human approvals, and audit records are embedded in the execution path. Detailed security profiles, PII, and egress controls are centralized in the Security Suite.
Policy gates with enforced controls
Blocking, approval routing, and alerting behavior is defined as policy and enforced directly in execution.
Approval orchestration and step-up auth
High-risk actions are routed to role-based approvals, with step-up MFA where additional assurance is required.
Audit chain and evidence generation
Decisions and control actions are captured as reviewable evidence for governance and compliance workflows.
Evidence via Observe
Incidents, playbooks, and the audit chain are part of live operations; decisions and approvals are stored as chained evidence.
Security Suite
Central security layer applied to every surface.
Security profiles, PII recognizers, egress control, RAG guard, and sandbox — Agentic AI, Secure Chat, and the SDK gateway share the same rules.
Profile-based guard
Thresholds, categories, and shadow mode across ingress, egress, RAG, and tool scopes; enforced via security.scan.
PII and secret masking
Partial, full, or KMS tokenize strategies; tenant-specific recognizer definitions.
Egress and tool safety
Allowlists, SSRF validation, and sandboxing constrain outbound calls and code execution.
RAG guard and quarantine
Retrieval injection defense and suspicious content isolation reduce data leakage risk.
Secure Chat
Every turn passes through guards before the vendor sees raw data.
Config-driven chat runtime: input guard, policy, PII masking, model call, output guard, and quality gate in one pipeline.
Config and capabilities
Vendor/model, masking strategy, security profile, budget; text, vision, web search, and document capabilities.
Mask → vendor → unmask
Personal data reaches the vendor as tokens; responses are unmasked on the tenant side.
Policy and quality gate
Input/output policy, violation levels; session- and message-level evidence.
Analytics and logs
Session tracking, violation reports, cost metrics, and API log integration.
Turn pipeline
Embed security and compliance in your app
Expose modules to external systems via a profile-based gateway.
Create a profile, pick modules, bind a security profile, publish — Python, TypeScript, Java, Rust, and Go SDKs are generated automatically.
Module catalog
Security, quality, compliance (GDPR/KVKK/HIPAA/EU AI Act), RAG, tool safety, and observability modules.
Gateway and key management
Rate limits, IP allowlists, live/test environments, version pinning; published snapshots are immutable.
SDK generation and registry
Multi-language client code after publish, plus package registry credential support.
Analytics and webhooks
Usage rollups, effective-units billing, and event webhook delivery.
Conversational AI and Knowledge Pool
Pipeline-based conversational operations and a shared knowledge pool.
Conversational AI pipelines independent from Agentic AI workflows; tenant-wide knowledge pool feeds RAG and dialogue flows.
Pipelines and templates
Draft/publish versioning, operational checklists, and session management.
Knowledge Pool
Shared tenant knowledge sources; common access for agents, conversational AI, and RAG layers.
Secure Chat integration
The same security profiles and policy engine apply to chat surfaces.
Publish via Connect
Event delivery to external systems through webhooks and the connector hub.
Observe and Connect
Production evidence and external system links.
Immutable audit chain, incidents/playbooks, SLO/KPI visibility; connectors and webhooks for integration.
Audit chain
Chained audit records with verification; incident evidence generation.
Incidents and SLO
Incident management, playbooks, burn rate, and KPI definitions.
Connector hub
Connectors including MCP; aligned with the Agentic AI tool registry.
Webhook delivery
Event-driven webhooks with retry and delivery logs.
One product, full operational lifecycle
The vertical lifecycle (build → runtime → govern) and horizontal services (SDK, Secure Chat, Observe) share tenant-wide security and audit layers.
Setup and readiness
Agents, prompts, tools, RAG sources, workflows, and intents are versioned as one delivery unit.
Execution and decisions
Runs execute in controlled modes, with optional deliberation on high-stakes decisions before action.
Control and evidence
Policy gates, human approvals, audit chain, and incident tracking are native to live operations.
Horizontal platform services
Secure Chat, SDK gateway, Conversational AI, and Observe — Security Suite profiles and audit evidence are shared tenant-wide.
Four-layer security architecture.
Security and compliance are not add-ons in Misel — they are core design principles of the system. Each layer operates independently, validates the one beneath it, and keeps the entire system under continuous oversight.
Agents & AI
Generative core
The individual or committee AI agent layer that executes tasks, calls tools, and accesses memory and retrieval systems.
Schedules agent runs, manages debate sessions, handles automated event triggers, and evaluation pipelines.
Defines agent access permissions, tool restrictions, and which outputs require human approval before proceeding.
Every decision and action recorded immutably. Meets legal, regulatory, and enterprise compliance requirements out of the box.
Let's talk.
See the same platform, end-to-end, on a 30-minute demo—with a scenario tailored to your industry.