The embedded agent platform for product teams

Make your product think.

Dezifi embeds AI agents inside your product — agents that listen to your customers, act on your data, and run on your stack. Multi-tenant from the first session. Reachable everywhere your customers already are.

Good evening
Here's what's happening across your workspace
Active Runs
48
284K total runs
Success Rate
99.2%
281.7K passed
Total Cost
$8.6K
428M tokens
Avg Latency
2.8s
across 281.7K runs
246
Agents
246 active
38
Workflows
38 active
312
Tools
312 connected
128
Knowledge
1,420 documents
Recent Runs
Global RevOps Orchestrator
Success2.4s$0.84
Claims Triage Multi-Agent System
Success3.1s$1.12
Compliance Evidence Collection Agent
Success1.9s$0.46

Connects with the systems your teams already use

140+ integrations available and expanding
Salesforce
Jira
GitHub
Slack
ServiceNow
HubSpot
Zendesk
Snowflake
Microsoft Teams
Outlook
Gmail
Datadog
Linear
Confluence
Okta
Workday
SAP
NetSuite
Asana
Notion
Google Drive
SharePoint
Twilio
Stripe
Postgres
MongoDB
BigQuery
Azure DevOps
Docker
Kubernetes
Intercom
Freshdesk
Salesforce
Jira
GitHub
Slack
ServiceNow
HubSpot
Zendesk
Snowflake
Microsoft Teams
Outlook
Gmail
Datadog
Linear
Confluence
Okta
Workday
SAP
NetSuite
Asana
Notion
Google Drive
SharePoint
Twilio
Stripe
Postgres
MongoDB
BigQuery
Azure DevOps
Docker
Kubernetes
Intercom
Freshdesk
The problem

AI demos are easy. Production execution is hard.

Most AI initiatives work in controlled demos. In real workflows teams hit governance, reliability, debugging, and accountability walls.

Unpredictable behavior

Agents act differently across runs with no clear constraints.

No visibility

Business and engineering teams cannot see what happened or why.

Unrestricted access

Security teams worry about agents touching sensitive systems.

No audit trail

Approvals, decisions, and tool calls are not logged for review.

The platform

One platform for orchestration, governance, and observability.

Dezifi provides the infrastructure to design, deploy, monitor, and govern AI agents across enterprise workflows.

Agent Orchestration

Design structured workflows with tools, conditions, approvals, and multi-step execution.

Governance & Policies

Define what agents can access, what actions they can take, and when humans must approve.

Observability

Track every agent run with complete traces, logs, latency, cost, and tool usage.

Enterprise Integrations

Connect agents to CRMs, ERPs, engineering tools, communication systems, databases and APIs.

Human-in-the-Loop

Approvals, reviews, and escalations before high-risk actions execute.

Multi-Agent Architecture

Specialized agents with their own roles, tools, policies, and execution boundaries.

Ships everywhere your customers are

One agent. Nine surfaces. No rebuilds.

Build the agent once on Dezifi. Reach your customers through whichever surface they actually use — without rewriting it for each one.

Server-to-server

MCP Server

Every agent is exposed as an MCP server. Claude Desktop, Cursor, Codex, and any MCP client call it natively.

Server-to-server

CLI

Terminal access for developers and ops. macOS, Linux, Windows binaries. One-line install.

Browser-embedded

Chat Widget

Drop a script tag, ship a chat experience in any web product. Origin-locked, theme-customizable.

Inbound triggers

Six ways events kick the agent off.

The agent does not care which one fires it. The same run, the same governance, the same audit trail.

In-product chat

Live chat sessions inside your application, scoped to the customer using it.

Email

Inbound emails to a dedicated address trigger the agent with the full thread as context.

Slack

Slack messages in shared channels or DMs invoke the agent and stream the response back.

Webhook

Any HTTP caller fires the agent. Pair with your existing event bus or workflow engine.

Schedule

Cron-style scheduled runs. Daily digests, weekly reviews, anything that should run on its own.

Manual

Operator-triggered runs from the dashboard with custom input — useful for ad-hoc and pilots.

Agent Builder

Design agents with structure, not vibes.

A 9-step builder defines the agent's identity, models, tools, knowledge, memory, voice, guardrails, and governance — every agent ships production-ready.

  • System prompt, reasoning pattern, output format
  • Multi-model: GPT, Claude, Gemini, fine-tuned LLMs
  • Tool & integration binding with scoped permissions
  • Memory, RAG knowledge bases, voice and guardrails
Step 9 of 9
100%
Agent Definition
Name, description, behavior
Language Models
Select and configure LLMs
3
Tools & Integrations
Add tools and capabilities
4
Skills
Capability packs
5
Knowledge Base
Configure RAG systems
Memory Systems
Configure agent memory
7
Voice Settings
Enable and configure voice
8
Guardrails
Runtime safety checks
Agent Definition
Agent Name
Global Finance Compliance Orchestrator
Reasoning
Chain of Thought
Output Format
freetext
Governance Policy
Enterprise Finance Controls · PROD
Guardrails
Strict · Regulated Workflows
Memory
Long-term · 365d · Encrypted
System Prompt
You are the Global Finance Compliance Orchestrator for a multi-entity enterprise. Review invoices, close-cycle artifacts, ERP exports, tax documents, and audit evidence; route exceptions to approvers; enforce policy boundaries; and prepare finance-ready summaries for controllership, treasury, and compliance teams across regions...
Language Models3
GPT-5.2 PrimaryT:0.2 · 256k
Claude 4.1 ReasoningPolicy fallback
Gemini 2.5 Pro VisionDocument parsing
Tools8
sap.read
netsuite.write.reviewed
snowflake.read
workday.lookup
sharepoint.retrieve
slack.notify.approvers
approval.request
audit.log.append
Workflow Designer

Multi-agent workflows, visually orchestrated.

Compose triggers, agents, decisions, and human approvals on a canvas. Run them as Workflow, Map-Reduce, or Manager-Worker patterns.

  • Triggers: Webhook, Email, Schedule, Slack, Manual, Chat
  • Branching, parallel fan-out, and approval gates
  • Versioned graphs with rollback and change history
  • Live test runs with full execution lineage
Global Incident Command Center
Production workflow for multi-region incident operations
ActiveRun SimulationPublish v24
WorkflowMap-ReduceManager-Worker
PagerDuty Webhook
Global incident trigger
Telemetry Aggregation
Logs, traces, metrics ingest
Change Intelligence
Release diff + blast radius
Customer Impact Agent
Revenue, SLA, and tenant impact
Severity Router
P1 / P2 / customer-impact pathing
Security Triage Agent
Threat intel and compromise checks
Executive RCA Agent
Cross-team root cause synthesis
Comms Orchestrator
Status page, Slack, customer comms
Rollback Planner
Automated remediation playbook
Incident Commander Approval
Ops, SRE, and security sign-off
Global Status Broadcast
Exec, customer, and partner updates
⚡ Trigger🤖 Agent✓ Approval⤴ Playbooks18 nodes · 32 edges
Policy Engine

Policy-as-code for every agent action.

Define what agents can do, what they can touch, and how strictly limits are enforced — at the workspace, agent, or workflow scope.

  • Tool allow/deny lists and scoped credentials
  • PII isolation and data privacy rules
  • Token, time, and cost execution limits
  • Hard or soft enforcement modes with audit trail
Step 1 of 6
17%
1
Basic Info
Name, version, scope
2
Tool Controls
Allow/deny tools
3
Data & Privacy
PII and isolation
4
Execution Limits
Tokens, time, costs
5
Behavior
Escalation rules
6
Review & Create
Review and create policy
Policy Identity
Define basic information about this policy
Policy Name *
Production Agent Policy
Version
1.0.0
Description
Defines security and cost limits for production agents handling customer data and CRM writes.
Scope & Enforcement
Scope
Agent — Applies to specific agent
Enforcement
Hard — Strictly enforced
salesforce.write
pii.mask
approval > $10k
Guardrails

Runtime safety checks that actually block.

Pick a protection tier or build your own. Guardrails inspect every prompt, tool call, and response — blocking dangerous content, leaks, and policy violations in real time.

  • Permissive · Balanced · Strict — pre-built tiers
  • PII detection, jailbreak detection, output validation
  • AI-powered detection for regulated industries
  • Per-agent overrides and live test playground
Set Up Guardrails
Choose a protection level to get started instantly
Permissive
Lightweight checks — warns but rarely blocks
Best for internal tools and development
3 checks active
See what's inside
RECOMMENDED
Balanced
Blocks dangerous content, warns on data leaks
Recommended for customer-facing agents
7 checks active
See what's inside
Strict
All checks active — AI-powered detection enabled
Best for regulated industries and fintech
13 checks active
See what's inside
Profile name
Balanced Guardrails
CustomizeApply Balanced Guardrails
Monitor & Trace

Every run, fully traceable. Every tool call, logged.

Production-grade observability designed for AI agents — see runs by status, drill into spans, replay decisions, and debug failures the way SREs debug services.

  • Status filters: total, running, succeeded, failed, pending
  • Per-run latency, cost, token, and tool span timeline
  • Approval & escalation history with reviewer identity
  • Searchable by Run ID, agent, workflow, or workspace
Runs
28/04/2026 · 12,480 total
Refresh
12,480 Total184 Running12,046 Succeeded168 Failed82 Pending
Run ID
Description
Submitted
Duration
Progress
Cost
91fd9533
Global RevOps OrchestratorAGENT
Apr 28, 02:05 PM
2m 14s
1/1
$1.84
a1d3f8e2
Claims Triage Multi-Agent SystemAGENT
Apr 28, 01:52 PM
1m 41s
1/1
$1.29
50ae7e76
Compliance Evidence Collection AgentAGENT
Apr 28, 01:41 PM
3m 08s
1/1
$2.42
96bdf5d1
Executive Escalation CopilotAGENT
Apr 28, 01:36 PM
54.8s
1/1
$0.76
420be34a
Enterprise Renewal Risk MonitorAGENT
Apr 28, 01:29 PM
1m 26s
1/1
$1.09
Analytics

Operational metrics for the AI workforce.

Aggregate volume, success rate, latency, token use and cost across agents and workflows. Slice by 24h, 7d, or 30d. Plug into your existing BI.

  • Daily run outcomes, cost & token consumption
  • Per-agent and per-tool performance breakdown
  • LLM call distribution across providers and models
  • Export to Snowflake, BigQuery, or your warehouse
Analytics
Performance metrics and execution insights
24h7d30d
Total Runs
48.2K
Success
99.18%
Avg Latency
2.8s
Tokens
42.8M
Cost
$18.4K
Workers
246
Runs Over Time
Daily execution volume by outcome
Success Failed
Cost & Token Usage
Daily spend and token consumption
Cost (USD) Tokens
Use cases

Start with one workflow. Scale across the enterprise.

Teams use Dezifi to operationalize AI agents in the workflows that matter most — then expand.

Build with us

Don't have an AI team? Use ours.

Most product teams have a roadmap line that says “ship AI agents” and no AI engineering bench to deliver it. Our team works alongside yours: we scope the first agent, build it on Dezifi, and hand it back to you owning it end-to-end.

Step 1

Scope

Short design phase with your team. We map the first agent — what it touches, what it can decide on its own, what success looks like in 90 days.

Step 2

Build

Our engineers build the first agent on Dezifi, paired with your engineers so they own it after handover. Guardrails, evaluations, and tenant isolation set up by default.

Step 3

Handover

Your team owns the agent forever. The platform stays. We are on call when you ship the next one — or when you need a second pair of hands on a hard one.

Tell us what you want to build

One agent, owned by your team in 4 to 8 weeks.

We work best with product teams who have a clear first agent in mind and want it shipped without spinning up a six-month platform-build first.

  • Designed against your real workflow, not a demo
  • Built on the platform you will keep using forever
  • Your team paired in from day one — they own it after

Get in touch

Send us the agent you want first.

The contact form opens your email client with the inquiry pre-filled. The message goes from your address to contactus@dezifi.ai — no servers in between.

Ship the first agent inside your product.

Bring us the agent your product team has been talking about. We will tell you what is realistic on Dezifi, what the first 90 days look like, and how the platform handles tenant isolation and governance.