01
Monitoring agents
Detect anomalies in your data and receive real time alerts when thresholds are breached.
Agentic Studio
Enterprise AI agentswithout the code
Create, deploy, and manage custom AI agents in minutes. Monitor data, automate workflows, and gain insights across your entire enterprise, powered by the LLM of your choice.
Agentic Studio · Agent builderDeploy in 15 minutes
LLM provider
- Anthropic Claude
- OpenAI GPT
- Google Gemini
- Meta Llama
- DeepSeek
Business rules
- ActionExecutes automatically
- ApprovalPauses for human signoff
- SecurityAdds monitoring
- ValidationEnforces data integrity
Execution priority
- 1Decision graphs
- 2Advanced scripts
- 3Business rules
- 4Default AI reasoning
60+
Feature modules
5
LLM providers
4
Support channels
50+
Enterprise app integrations
Agent templates
Prebuilt agent templates
Choose from enterprise ready templates and customize them for your specific needs
02
Summarization agents
Get automated daily summaries of key metrics and changes in your business data.
03
Action agents
Automatically trigger updates and actions based on detected events in your systems.
04
Q&A agents
Answer natural language questions about your data using advanced AI models.
Tier 1: hero features
Lead with these capabilities
No code / low code AI agent builder
Build and deploy AI agents in 15 minutes, no engineering required. Visual rules editor, drag and drop logic, and point and click configuration.
- Visual drag and drop agent canvas
- Point and click logic configuration
- Deploy in 15 minutes
- Prebuilt enterprise templates
Multi LLM provider support
Choose your AI backbone: Anthropic Claude, OpenAI GPT, Google Gemini, Meta Llama, or DeepSeek. Mix providers per agent without lock in.
- Anthropic Claude
- OpenAI GPT
- Google Gemini
- Meta Llama and DeepSeek
Business rules engine
Turn policy into agent behavior in plain language, no code required. Four rule types execute in a deterministic, priority ordered sequence with live success tracking.
- Action, Approval, Security and Validation rule types
- Priority ordered, explainable execution
- Visual AND/OR condition builder
- Live execution and success rate tracking
Visual decision graphs
Model complex business logic visually with an interactive node canvas. Drag, connect, and test decision trees that execute at runtime via a proven rules engine (GoRules/JDM).
- Interactive node canvas
- Drag and connect decision trees
- GoRules/JDM rules engine
- Real time runtime execution
Intelligent human escalation
Real time sentiment scoring, failure loop detection, and multi layer escalation triggers automatically hand frustrated customers to a human agent, with an AI generated conversation summary already waiting for them.
- Real time sentiment scoring
- Failure loop detection
- Multi layer escalation triggers
- AI generated handoff summaries
RAG powered knowledge base
Upload PDFs, Word docs, Excel sheets, images (OCR), logs, CSVs, and Markdown. The platform chunks, embeds, and semantically searches documents to inject live context into every agent response.
- PDF, Word, Excel, CSV, Markdown
- Image OCR ingestion
- Semantic search and chunking
- Live context injection
Tier 2: key differentiators
What sets us apart
01
Cloud connector crawling
Connect Google Drive, OneDrive, Dropbox, SharePoint, and Confluence. Crawls and indexes your existing documents into the RAG pipeline automatically, and stays permission aware.
02
MCP integration
Connect agents to external tools like GitHub, Atlassian Jira/Confluence, and ServiceNow using the open MCP standard. Agents can read tickets, create issues, and take real actions.
03
Live chat with AI routing
An AI powered intent engine automatically selects the right agent for every incoming chat session, with no manual routing rules to maintain.
04
Orchestrator agents
Coordinate fleets of specialized subagents in complex workflows. One orchestrator breaks down tasks, delegates to experts, and assembles results.
05
Voice and video capabilities
Multimodal agents that listen (speech to text), speak (text to speech), and see (image and video analysis via Claude Vision and GPT-4 Vision).
06
External platform integrations
Deploy agents everywhere: Amazon Alexa, Google Assistant, Twilio Voice/SMS, Microsoft Teams, Slack, Cisco Webex, Google Chat, PagerDuty, and xMatters.
Tier 3: enterprise depth
Built for enterprise
Secure multi tenant architecture with role based access control. Your agents can only access the data you have permissions for.
Enterprise RBAC
35+ granular permissions across 8 categories. System roles (Owner, Admin, Member) plus fully custom roles. Object level access control and a complete audit log.
Multi tenant workspace isolation
Every organization's data is fully isolated across 22+ tables. Personal and team workspaces with real time context switching.
Active Directory integration
Automate AD operations (account unlock, password reset) directly from AI agents, triggered from Live Chat, Playground, or scheduled tasks. Full audit trail included.
Agent API keys
Expose any agent as a secure REST API. Keys are encrypted, usage tracked, and revocable, suitable for embedding into third party products.
Task automation and scheduling
Event driven triggers, cron scheduled tasks, and batch processing. Execution history and a background scheduler service included out of the box.
Multi agent collaboration
Shared workspaces, agent to agent messaging, delegation hierarchies, and consensus voting for decisions that benefit from multiple AI perspectives.
Advanced scripting with Monaco Editor
Full JavaScript editor with AI powered code generation for power users who need logic beyond what visual rules can express.
Platform deep dive
60+ modules, one connected platform
From the first message on a website widget to a quarterly cost report on an executive's desk, every capability below lives inside one data model. Select a suite to see the full breakdown.
High impact: features that most directly change resolution speed, safety, and ROIStandard: operational depth for managers, agents, and analysts
AI Agent Studio and knowledge (RAG)
Design an agent's decision logic the way your team thinks (visually, declaratively, or in code), grounded in your own documents.
01.1
Visual and low code logic
Multiple logic modes so teams can start no code and add precision as needed.
High impact
- Drag and drop visual decision graphs (JSON Decision Model / JDM) let nondevelopers map branching logic exactly as they'd whiteboard it, executed by an industry standard rules engine
- Low code business rules with AI assisted generation: describe a rule in plain English and the platform drafts structured, validated logic
- Four rule types: Action rules execute automatically, Approval rules pause for human signoff, Security rules add monitoring, and Validation rules enforce data integrity, so policy isn't forced into a one size fits all shape
- Priority ordered, explainable execution: every rule carries an explicit priority, so when several rules could apply the outcome is deterministic and never a black box, with live execution counts and success rates visible in the list view
- 15 minute agent creation: from blank canvas to a deployed, testable agent in about fifteen minutes
Standard
- Enterprise condition builder: a visual AND/OR builder combines criteria like department, role, employee status and login pattern without writing a query
- One click enable/disable lets teams pilot a new rule on a small scope before turning it on organization wide, with no redeploy required
- Built in test dialog and version history: every rule can be tested against sample data before activation, and rule versions are tracked so a team can review what changed and roll back if needed
- Advanced scripts via a full Monaco code editor (the engine behind VS Code) with AI code generation for complete programmatic control
- Enterprise actions: a reorderable, multistep action system triggers notifications, API calls, and escalations in a defined sequence, with auto execute on trigger for unattended runs
- AI Agent Playground: a dedicated sandbox to converse with an agent under construction and inspect its reasoning before go live
- Execution priority: decision graphs evaluate first, then advanced scripts, then business rules, falling back to default AI reasoning
01.2
Case study: automating Active Directory operations
A real customer configuration: one agent manages the full AD user lifecycle end to end through eight coordinated business rules.
High impact
- Get AD User and Create AD User run as Action rules, while Manager Change and Account Reactivation trigger Approval and Security review before anything executes
- Privileged Role Assignment gets Enhanced Monitoring, Employee ID gets a Validation data integrity check, and Concurrent Login Detection raises a real time Security alert
Standard
- Every critical operation is audited automatically. IT and HR get a self service front door for account requests that used to need a ticket, while security and compliance get more oversight than a manual process, not less
01.3
Multi LLM intelligence and knowledge (RAG)
Agents reason with the right model for the job and ground answers in the organization's own documents.
High impact
- Multi LLM provider support: Anthropic, OpenAI, Google Gemini, Meta Llama and DeepSeek through one centralized configuration, avoiding vendor lock in
- Unstructured data ingestion: PDF, Word, Excel, images (with OCR), text, logs, JSON, CSV and Markdown all attach to an agent as a live knowledge source
- Hybrid search RAG pipeline: sentence aware chunking, synonym aware embeddings, and a hybrid of keyword and semantic (cosine similarity) search
Standard
- Per agent tuning: each agent has its own result count and similarity threshold, so a compliance agent can be stricter than a general FAQ agent
- Knowledge chat and search: a standalone experience to query the knowledge base directly, independent of a live conversation
- Structured output validation: machine readable model responses are schema validated with automatic self correction retries
Multi agent orchestration, A2A and MCP
Agents aren't isolated chatbots. They run on a real graph based execution engine and can call each other and external systems.
02.1
LangGraph runtime and agent to agent protocol
A stateful execution backbone with standards based agent discovery.
High impact
- LangGraph execution backbone: every agent runs on a stateful graph runtime with per conversation memory checkpointing for reliable, inspectable multiturn reasoning
- Agent to Agent (A2A) protocol implements the Google A2A open standard. Each agent publishes a machine readable "Agent Card" describing its skills so peers can find and delegate automatically
- Multi agent collaboration: a framework for coordinating several specialized agents on one task with shared context, plus a dedicated Orchestrator agent type for complex workflows
Standard
- Model Context Protocol (MCP): real, dynamic tool discovery connects agents to GitHub, Atlassian, ServiceNow and custom MCP servers so an agent can take real action
- Test Intelligent Orchestrator: a dedicated testing surface for validating multi agent handoffs and orchestration logic before go live
- Agent API keys: secure, encrypted key issuance with usage tracking for external systems to call an agent programmatically
02.2
Intelligent routing and live handover
Getting a conversation to the right agent the first time is the single biggest driver of resolution speed.
High impact
- Semantic intent routing uses real semantic embeddings of each agent's capability profile (not brittle keyword rules), so the closest match wins even with unpredictable phrasing
- Automatic AI to AI handover transfers mid conversation when a better fit agent is detected, carrying prior context so the customer never repeats themselves
- Routing rules engine: managers configure explicit rules by language, channel, keywords, business hours and skills
Standard
- Routing simulation tests a rule set against sample conversations and shows the full ordered evaluation trail before publishing
- Knowledge base fallback answers from grounded content rather than guessing when no agent confidently matches
- Loop protection detects and stops recursive transfer loops with a graceful fallback response
Human agent workspace and omnichannel
When a conversation needs a person, agents get a purpose built workspace spanning every channel customers already use.
03.1
Live chat and the unified agent dashboard
High impact
- Live chat console with real time two way messaging and live token streaming: agents watch a suggested AI reply compose before sending or editing it
- Agent and human agent dashboards give purpose built views of assigned queue, conversation status and workload at a glance
- Escalation and human handoff: AI agents escalate to a human queue with one action, and the customer facing conversation continues seamlessly
Standard
- Canned responses with AI suggestions: a ranked, contextual library plus an AI drafted custom reply when nothing fits
- Contact and conversation history gives agents complete history before they type a word
- Thread aware reopening retains full prior context when a customer replies days later
03.2
Omnichannel coverage
High impact
- Embeddable chat widget: a single script tag adds a fully branded AI chat bubble to any website, configured visually with a live preview
- Email channel: inbound email via webhook (Mailgun/SendGrid) or IMAP polling, threaded into the same conversation model as chat
Standard
- Facebook and Instagram messaging connects Meta platforms via webhook, resolving the correct organization automatically per page
- Saved credential protection prevents managers from accidentally clearing a working channel integration
- Deep reply chain threading keeps long running, deeply nested "Re: Re: Re:" email conversations correctly grouped
03.3
Enterprise application integrations
High impact
- 50+ out of box, enterprise grade application connectors let agents read and act on live data mid conversation, including XpediOo, ServiceNow, Workday, SuccessFactors, BMC Helix, Zoho HR, Zoho CRM, SAP, and Oracle
- Prebuilt connectors cover ITSM/ITAM, HRIS, CRM, ERP, and ITOM systems, so a conversation can look up, create, or update a record without leaving the chat
Standard
- Credential vaulting and connection health checks per integration, with masked secrets and one click reconnect
- New connectors are added continuously; the Platform Integrations Hub exposes the full, current catalog
03.4
Workforce management
High impact
- Queue settings configure how conversations queue and how auto assignment behaves, switchable mid shift
- SLA management defines response and resolution targets per queue or priority, with visibility into breaches before they happen
Standard
- Agent teams and skills management groups and tags agents so routing matches the right expertise, not just the next available body
- Business hours drive after hours routing, auto replies and escalation automatically
- Capacity aware reassignment guards against overloading an already full agent
- Conversation tags support flexible categorization for reporting, routing and follow up campaigns
Quality, coaching and customer experience
Automation only scales when you can measure whether it's working, and when supervisors can help agents in the moment.
04.1
Quality assurance and confidence gating
High impact
- Confidence gating scores every AI response in real time with a blended heuristic + LLM model; low confidence responses route to a human instead of sending as is
- QA scoring computes and stores structured quality scores per conversation across the whole AI and human workforce
Standard
- Failure visibility and retry surfaces a persistent failure indicator and a clear retry path when a channel or AI call fails
- Language detection resilience keeps European language conversations from being silently mislabeled as English, and retries automatically once an outage clears
04.2
Supervisor tools: coaching and live monitoring
High impact
- Whisper mode lets supervisors send private, real time coaching notes into a live conversation that only the agent sees
- Supervisor live queue overview gives a real time dashboard of every in progress conversation and which team it routed to
Standard
- Supervisor monitoring drops into any live conversation to observe quality without disrupting the agent's flow
- Reassignment controls offer one click reassignment respecting skills, capacity and business hours
- Agent notifications alert agents to new assignments via sound and browser notices, even when the tab isn't focused
04.3
Customer experience: CSAT, sentiment and memory
High impact
- CSAT and satisfaction surveys capture a post conversation score with zero login friction, feeding a dedicated analytics view
- Churn risk alerts flag conversations showing churn risk signals in real time, broadcast directly to agent and supervisor views
- Next best action (NBA) recommends the agent's next move (offer a discount, escalate, follow up) based on conversation context
Standard
- Real time emotion detection analyzes tone in the background and surfaces frustration before it escalates
- Customer memory builds durable, per customer context across conversations so returning customers aren't starting cold
Analytics, BI and AI driven pattern detection
Dashboards for the questions support leaders actually ask, plus AI that mines conversations for patterns a human analyst would take weeks to find.
05.1
Analytics and business intelligence
High impact
- Chat analytics covers volume, resolution time, channel mix and outcome trends, filterable by team, agent and time range
- Agent scorecards compute per agent performance summaries with daily trend detail directly from conversation history
- LLM cost tracking logs estimated token usage and cost by model, giving finance grade visibility per conversation, agent and organization
Standard
- CSAT analytics segments satisfaction trends by agent, team or channel to catch quality drift early
- Staffing forecast computes on demand staffing recommendations from historical volume and external calendar events
05.2
AI analytics: clustering, anomalies and predictive signals
- Topic clustering automatically groups conversations into emerging topics, surfacing what customers are contacting support about this week vs. last
- Anomaly detection flags unusual spikes or patterns in volume or outcomes
- Conversation intelligence extracts deeper structured insight across the corpus, feeding dashboards and proactive alerts
- Weekly briefing automates a Monday summary of volume, quality and notable trends for leadership
- Competitor intelligence detects and logs competitor mentions inside conversations for product and sales visibility
- Knowledge gap detection identifies questions the knowledge base couldn't answer well and auto drafts a KB article to close the gap
Governance, security and compliance
Enterprise buyers need proof, not promises, and the platform is designed to serve more than one tenant safely.
06.1
Compliance, GDPR and audit trail
High impact
- Compliance export generates auditor ready PDF exports of conversation records and quality data on demand, without exposing the underlying database
- GDPR data management provides dedicated tooling for data subject requests: locating, exporting and deleting a customer's data across the platform
- Enterprise RBAC: granular, resource level role based access control with custom roles and full audit logging of who accessed or changed what
- AI safety guardrails: a defense in depth content moderation stack (safety middleware, LLM layer validation, a dedicated safety engine) detects prohibited content, jailbreaks and prompt injection before a response reaches a customer
Standard
- Outbound trigger governance runs automated outbound messages on a governed scheduler with delivery tracking, avoiding uncontrolled or duplicate outreach
06.2
Security and multi tenancy
High impact
- Full workspace isolation: every organization's agents, conversations, rules and files are isolated at the data layer, so no cross tenant visibility is possible by design
Standard
- Active Directory integration automates AD operations (account unlock, password reset) driven by action based business rules, with a full audit trail
- Voice and video multimodal support extends agents beyond text with speech to text, text to speech and computer vision based analysis
- Secure agent API keys provide encrypted key issuance with per key usage tracking for safe programmatic access
06.3
Observability and enterprise reliability
- OpenTelemetry instrumentation captures every agent execution, peer to peer call and message processing step as a structured trace span
- Live observability dashboard shows conversation volume, latency, token usage and cost, plus a color coded per agent performance table with a live span feed
- First response time tracking captures time to first response per conversation automatically as a core SLA metric
- External tracing integration offers one flag integration with third party tracing platforms such as LangSmith
Automation, reporting and extensibility
Agents don't just chat. They drive multistep business processes, close the knowledge loop, and connect to the rest of the stack.
07.1
Workflow automation and task scheduling
- Visual workflow canvas: an n8n style, drag and drop builder with natural language driven execution for multistep processes
- Task automation and schedules handle recurring or batch work via event driven triggers and a cron based scheduler
- Workflow playground offers a safe environment to test workflow logic against sample data before publishing
- Execution history gives a complete, searchable log of every agent and workflow execution for debugging and review
07.2
Proactive intelligence and knowledge management
High impact
- Knowledge base: centralized, agent attachable knowledge sources spanning documents, spreadsheets, images and structured data
Standard
- Automated weekly briefing delivers a fixed schedule Monday summary so leadership always starts the week informed
- Proactive messaging reaches customers based on defined conditions rather than waiting for them to contact support
- Staffing recommendations forecast needs on demand using historical patterns plus external event data
- Knowledge gaps surface the questions the knowledge base is failing to answer, ranked by frequency and impact
- Auto drafted KB articles draft a knowledge base article automatically once a gap is resolved through a real conversation
07.3
Simulation, reporting and integration ecosystem
High impact
- MCP server management connects any Model Context Protocol server (GitHub, Atlassian, ServiceNow or custom) with tools instantly callable by agents
- LLM cost tracking and attribution turns "AI is a black box cost" into a per model, per agent, per conversation line item budget
Standard
- Conversation replay steps through any historical conversation to understand exactly why an agent responded the way it did
- Routing rule simulation runs a candidate rule set against test conversations with the full ordered evaluation trail
- Scheduled reports and shareable report links deliver PDF/CSV reports on a recurring schedule and let stakeholders view them without a platform login
- Platform Integrations Hub, API key management and a standards compliant Agent Card discovery endpoint round out the integration ecosystem
07.4
Integrations and tools hub
Business Rules and Decision Graphs define when and why something should happen. The Integrations and Tools hub is how an agent actually reaches into other systems mid conversation.
High impact
- Prebuilt enterprise connectors: dozens of ready made integrations (ServiceNow, Workday, Salesforce, Microsoft Teams, Active Directory, and more) connect existing systems in minutes instead of custom API code
- Deep tool catalogs per system: each integration exposes dozens of specific callable actions, from "Get Worker Compensation" to "Approve Absence," not just a generic API passthrough
Standard
- Guided setup, OAuth or manual: sensitive connections use a guided OAuth 2.0 flow while simpler ones accept scoped credentials directly; secrets are stored securely and never displayed after entry
- Health monitoring and testing: a dedicated health view shows the live status of every connected integration, with one click connection tests so issues surface before they affect a customer
07.5
Integration categories at a glance
12 integration categories span every major system an enterprise support or operations team touches, with 40+ callable tools available from a single HR class connector alone.
High impact
- ITSM (ServiceNow and similar platforms): create, update and track incidents and change requests
- Identity (Active Directory and identity providers): create and manage user accounts, audit access, monitor logins
- HR (Workday class HRIS platforms): worker lookups, pay and benefits data, absence and leave requests, performance goals
- CRM (Salesforce class platforms): look up accounts and opportunities, update records, log activity
Standard
- Collaboration (Microsoft Teams and similar tools): send messages, create meetings and channels, manage members
- DevOps (source control and CI/CD platforms): manage issues, pipelines and deployments
- Cloud (cloud infrastructure providers): query and manage cloud resources
- Security (security and monitoring platforms): pull alerts, trigger reviews, escalate incidents
- Helpdesk / ERP / Data / Platform (ticketing, ERP, data and internal platform tools): end to end coverage across finance, ops and internal systems
Why it matters
“Most vendors force a choice between an AI agent builder and a help desk. XpediOo treats both as one conversation lifecycle: a chat can start with an AI agent, escalate to a human, get scored for quality, feed analytics, and trigger proactive follow ups, without leaving the platform or reauthenticating context.”
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