One fully native stack.
Zero external dependencies.
OCP owns every layer — from the acoustic model to the agentic orchestration engine — eliminating third-party data flows, token cost exposure, and compliance blind spots.
Unlike platforms assembled from third-party ASR, LLM, and TTS APIs, OCP is a vertically integrated stack. Omilia's proprietary models are fine-tuned for enterprise voice — not adapted from general-purpose frontier models. This means sub-second latency that external API chains cannot achieve, and a certified security perimeter that zero-dependency architecture uniquely enables.
Deployments run on Omilia-managed AWS infrastructure or on dedicated bare-metal nodes within a customer's own data center. In both modes, no customer utterance data leaves the certified environment — a requirement that PCI Level 1 and FedRAMP mandates.
Fully Native Speech Pipeline
Proprietary ASR → NLU → Dialog Manager → Lexis TTS. No third-party STT or TTS APIs, ever. Utterance data stays inside the certified perimeter at every hop.
Autonomous Reasoning & Planning
Task Agents resolve complex, multi-step customer requests end-to-end — handling intent shifts, tool failures, and edge cases in real time, without human intervention.
Specialized, Not Frontier
Domain-specific and task-specific fine-tuned models for NLU, retrieval, and spoken summarization. Smaller specialized models outperform frontier LLMs on voice tasks at a fraction of the inference cost.
OAuth2 / API key auth
Real-time transactional data
CRM · ERP · Ticketing · DB
One integration, many tools
Policy & compliance docs
Semantic similarity lookup
- Account & transaction data
- Order & shipment status
- Claims & case records
- Billing & payment data
- Salesforce CRM
- ServiceNow ticketing
- SAP / NetSuite ERP
- Custom data warehouses
- Product & policy docs
- Compliance documentation
- Troubleshooting guides
- SOPs & training materials
Every layer engineered for enterprise voice.
Six native capability domains — all included, all proprietary, all running inside your certified security perimeter.
Blended Deterministic & Autonomous AI
Deploy fully deterministic flows, fully autonomous agents, or a hybrid blend — per use case, in the same runtime. No re-platforming when governance requirements shift.
- Deterministic Planning: static workflows with guaranteed governance
- Autonomous Planning: dynamic real-time plans from caller intent
- Agentic NLU Fallback: GenAI recovery layer for deterministic breakdowns
- Context tracking across channel switches with full state carryover
Autonomous Task Agents
Purpose-built agents that handle complex, multi-step customer interactions end-to-end — from intent detection through system actions and confirmation — without any human involvement for in-scope tasks.
- Resolves complex requests involving multiple backend systems in a single interaction
- Adapts in real time when customer intent changes or systems return unexpected results
- Operates within defined governance boundaries — automatically escalates out-of-scope requests
- Full interaction audit trail for every resolved task
Lexis Generative TTS
OCP's native neural text-to-speech engine — included at no additional cost for Agentic Voice customers. Deep neural network synthesis with emotion, rhythm, and real-time streaming. No utterance data sent to third-party TTS providers.
- Ultra-realistic voice generation with pacing, intonation, inflection
- Voice cloning & custom persona design from short audio samples
- Real-time streaming with low-latency pipeline for live agents
- Custom pronunciation dictionaries for financial & domain terminology
OCP Knowledge Engine (RAG)
Retrieval-augmented generation purpose-built for voice — low latency, hallucination-guarded, grounded in enterprise knowledge sources. MCP-native connector ecosystem replaces bespoke integrations.
- Ingests PDFs, SOPs, FAQs, and API specifications natively
- Confidence thresholds trigger clarification or escalation — not hallucination
- Offline RAG mode with zero LLM generation risk for supervised retrieval
- Hierarchical and flat data structure support
Agentic Self-Learning Pipeline
Every live conversation feeds an offline learning engine that continuously discovers new resolution patterns, improves automation performance, and reduces operational cost — without touching the live interaction path.
- Identifies new automation opportunities directly from live interaction data
- AI-assisted flow authoring: generates draft automation from transcripts, SOPs, and API specs
- Developer Co-Pilot: gap flagging, flow suggestions, and assisted build tools
- Human-in-the-loop approval gates before any change reaches runtime
Unit Economics & Cost Control
Full stack ownership eliminates the token burn problem. One price per resolved interaction — regardless of agentic steps taken. Self-learning codifies patterns offline, reducing LLM invocations in runtime over time.
- Outcome-based pricing: pay per resolved interaction, not consumed compute
- No third-party LLM dependencies — no token pricing volatility exposure
- Budget certainty: volume scales proportionally, not exponentially
- Self-learning reduces runtime LLM calls as patterns are codified deterministically
OCP Orchestration & Knowledge Engine
The agentic intelligence layer between callers and enterprise systems. Specialized GenAI models — not frontier APIs — process intent, plan tool sequences, dispatch calls in parallel, and synthesize grounded spoken responses within voice-safe latency budgets.
- Parallel async tool dispatch across APIs and MCP servers simultaneously
- Result synthesizer grounds responses in retrieved data before generation
- Hallucination guardrails enforced in real time with confidence scoring
- Context window management optimized for multi-turn voice dialogs
Intent Router
Classifies caller intent in real time, routing between deterministic flows and autonomous execution paths based on confidence scoring and governance rules
Tool Planner
Determines which tools to invoke, in what order, and with which parameters — dynamically re-planning when intermediate results change the required path
Parallel Dispatch
Async multi-tool execution enables simultaneous API calls, MCP lookups, and knowledge retrievals — delivering sub-300ms aggregate resolution within telephony SLA
Specialized Models
Fine-tuned for NLU, retrieval, and spoken summarization. Domain-constrained models eliminate the hallucination surface area inherent in general-purpose frontier LLMs
Genuine autonomy.
Not prompt chaining.
Each Task Agent is built for a specific interaction type — knowing what it can do, what systems it can access, and when to escalate. No fixed scripts. No brittle decision trees.
Task Agents are purpose-built AI agents, each configured for a specific type of customer interaction — such as dispute resolution, account changes, or policy lookups. Each agent knows which systems it can access, what it is authorized to do, and when it must escalate to a human.
Unlike rigid scripted bots, Task Agents handle real-world complexity: when a caller changes their request mid-interaction, when a backend system returns an unexpected result, or when multiple systems must be queried in sequence, the agent adapts and continues — without dropping the interaction.
Every automated interaction is fully auditable. Each system action, decision point, and outcome is logged with complete attribution — enabling compliance reporting without operational overhead.
End-to-End Task Resolution
Handles complete customer tasks — from understanding the request to taking action in backend systems and confirming the outcome — within a single voice interaction
Real-Time Adaptability
Adjusts to caller intent changes, unexpected system responses, and mid-conversation pivots without losing context or dropping the interaction
Defined Governance Boundaries
Each agent operates within explicitly configured authorization limits — automatically escalating to a human agent for any task outside its defined scope
Enterprise System Integration
Connects to customer APIs, MCP servers, CRMs, and knowledge bases — authorized integrations defined per agent and executed securely within OCP's certified perimeter
Complete Auditability
Every action, system call, and decision is logged with full attribution — providing a traceable record of every automated outcome for compliance and operational review
Automated Quality Assurance
Pre-production testing validates agent behavior against real-world interaction patterns before any configuration reaches live customer traffic
The platform learns from
every conversation.
OCP's offline self-learning pipeline continuously discovers new resolution patterns, auto-generates Playbooks, and improves automation performance — without modifying the live runtime.
Ingest & Analyze
Live interactions are analyzed by the self-learning engine, which continuously identifies where automation could succeed and surfaces recurring resolution patterns from thousands of real customer conversations.
Generate Automation
Omilia's AI builds new automation drafts from discovered patterns, ingesting call recordings, transcripts, SOPs, and API specifications. The platform does the heavy lifting — operators review and refine, not engineer from scratch.
Human Approval Gate
Every suggested automation or update is reviewed, edited, approved, or rejected by a business operator before deployment. The platform never auto-deploys changes to the live runtime without explicit human authorization.
Deploy & Improve
Approved changes are validated against pre-production quality checks before reaching live traffic. Automation performance improves continuously — and as more interactions are codified deterministically, runtime AI costs decrease over time.
From raw call data to
production autonomous agents.
Three phases from contract signature to live resolution — with no rebuild required when adding new use cases or upgrading from deterministic to agentic.
Bootstrap & Configure
OCP ingests existing call recordings, transcripts, SOPs, and API specifications. The AI Bootstrapping engine automatically generates initial dialog flows, intents, and training data — reducing deployment timelines from months to weeks. NLU achieves 95%+ intent accuracy before a single manual training example is added.
Integrate & Deploy
Task Agents are wired to enterprise APIs and MCP servers via the OCP Orchestration Engine's tool schema layer. The OCP Orchestrator routes between deterministic miniApps® and agentic execution paths — no re-platforming required when blending both. CCaaS connectors (NICE, Genesys, Amazon Connect, RingCentral) activate in the same deployment.
Monitor & Improve
OCP monitoring surfaces confidence signals, flags low-certainty interactions, and feeds the self-learning pipeline continuously. New automation is auto-suggested from live data, reviewed by operators, and validated before reaching production. Comprehensive performance and governance data is retained to satisfy enterprise audit and regulatory reporting requirements.
5 structural advantages
competitors cannot replicate.
Built over 23+ years for regulated industries where architectural shortcuts have compliance consequences.
Blended Deterministic & Autonomous AI
The only platform that natively supports deterministic, generative, and hybrid deployment modes in a single runtime — without rebuilding applications when governance requirements evolve.
Enterprise-Grade Security & Compliance
PCI DSS Level 1 + FedRAMP-ready + SOC 2 Type II + ISO 27001 simultaneously. Walled garden architecture with zero third-party data sharing — the only configuration that satisfies regulated financial, healthcare, and government mandates.
Tech Sovereignty & Fastest Time to Value
Full stack ownership — no commercial dependency on any external AI provider. 340+ pre-built NLU intents for financial services. 95%+ Day 1 intent accuracy with AI Bootstrapping from existing transcripts and SOPs.
Voice-Native Speech-to-Speech Pipeline
Built for voice from the ground up — not a text-first platform adapted for telephony. Proprietary ASR, NLU, and Lexis TTS create a single latency-optimized pipeline with no external API handoffs and no utterance data egress.
Self-Learning Closed Loop
Offline self-learning continuously discovers resolution patterns from live interactions and codifies them as deterministic automation — reducing AI runtime costs over time. The platform gets cheaper to run as it gets smarter.
Fully managed SaaS or
dedicated bare metal.
OCP is available as a fully managed SaaS on Omilia-operated AWS infrastructure, or as an on-premise bare-metal deployment inside your own data center for Tier 1 financial institution mandates.
Omilia Cloud Platform
Fully managed, multi-tenant SaaS on Omilia-operated AWS infrastructure. Omilia manages model versioning, infrastructure scaling, compliance auditing, and uptime SLAs. Zero operational overhead for the customer.
Infrastructure
Omilia-managed AWS, multi-region, auto-scaling
Uptime SLA
99.9%+ guaranteed with full monitoring and alerting
Compliance
PCI L1, SOC 2 T2, ISO 27001, HIPAA, GDPR
Updates
Continuous model and platform updates managed by Omilia
On-Premise Deployment
Dedicated bare-metal nodes deployed inside the customer's own data center or private cloud. Designed for Tier 1 financial institutions and government agencies with strict data residency, air-gap, or regulatory requirements.
Infrastructure
Customer data center or private cloud, Omilia-supported
Data Residency
Full data sovereignty — no traffic leaves customer's perimeter
Compliance
FedRAMP-ready, Cyber Essentials, custom regulatory frameworks
Model Control
Customer-versioned models, isolated upgrade cycles
MCP-native. API-agnostic.
Zero custom connectors.
The OCP Orchestration Engine connects to enterprise systems via Model Context Protocol (MCP), REST, GraphQL, and SOAP — with standard auth patterns and no bespoke connector development required.
OCP's integration layer is built on MCP as its primary standard. MCP replaces per-enterprise bespoke connectors with a standardized tool interface — reducing attack surface, eliminating maintenance overhead, and enabling a growing shared ecosystem of integrations that customers get automatically.
For systems not yet on MCP, OCP executes tool calls via standard REST, GraphQL, and SOAP endpoints with OAuth 2.0, API key, and custom auth patterns. Parallel async dispatch allows the OCP Orchestration Engine to invoke multiple tools simultaneously — keeping total round-trip time within sub-300ms voice latency budgets even when multiple backend systems are involved.
Context is tracked throughout each interaction and persisted as attached data to CCaaS handoffs — ensuring agents receiving escalated calls have full interaction history without the caller repeating themselves.
Model Context Protocol (MCP)
Primary integration standard. Standardized tool schemas, automatic ecosystem updates, reduced attack surface. CRM, ERP, ticketing, and database systems available out of the box. No custom connector code.
REST / GraphQL / SOAP
Full support for OAuth2, API key, and custom auth patterns. Bespoke enterprise endpoints supported with standard parameter configuration. Real-time transactional data retrieval.
CCaaS Connectors
Native connectors for NICE CXone, Genesys Cloud, Amazon Connect, RingCentral, Talkdesk, and 8x8. Context passed as structured attached data on escalation — caller does not repeat information.
Knowledge Ingestion APIs
Ingest PDFs, policy documents, SOPs, and product FAQs via API or direct upload. OCP structures unstructured content into AI-indexed knowledge layers. Supports flat and hierarchical data structures.
The walled garden approach.
Full auditability. Zero black boxes.
OCP's all-in-one architecture keeps all data within the platform with zero third-party sharing — enabling certifications competitors cannot achieve while providing full decision auditability at every level.
For regulated industries, Omilia is the only viable choice for voice automation at scale. Customer data never leaves OCP's infrastructure — no third-party AI providers, no hidden data flows. The walled garden architecture is what makes simultaneous PCI Level 1 and FedRAMP-ready certification possible: both require data sovereignty that external API dependencies break.
OCP enforces multi-layer hallucination prevention. For transactional use cases — payments, transfers, authentication — deterministic execution paths eliminate generative risk entirely. For generative responses, confidence thresholds trigger clarification questions or agent escalation before any uncertain output is delivered. The platform is designed to ask rather than guess — systematically favoring accuracy over volume.
Every automated decision is logged with full attribution. Audit infrastructure spans multiple retention tiers, satisfying both operational review and multi-year regulatory reporting requirements.
Full Platform Audit Trails
All OCP platform activity logged with user-level attribution — model updates, configuration changes, access events. Satisfies enterprise change management and regulatory audit requirements.
Complete Interaction Records
Every automated interaction — including all system actions and outcomes — retained with full traceability. A complete, attributable record of every automated decision is available for compliance review.
Long-Term Performance Data Retention
Aggregated model and application performance metrics retained to satisfy longitudinal governance reporting and multi-year regulatory review requirements.
Pre-Production Quality Validation
All model and configuration updates pass automated quality checks before reaching production — validating accuracy, consistency, and behavioral adherence prior to any live deployment.
Real-Time Sensitive Data Redaction
Inline PCI-compliant masking and adaptive redaction. Sensitive values irreversibly masked before storage or logging. RBAC enforced across all platform functions with mandatory human review for model updates.
One price. Per resolved interaction.
No token consumption billing. No compute overage. No surprises. Costs scale with outcomes — not with the number of agentic steps or LLM calls required to reach them.
Conversational Voice
Foundational IVA platform for structured, deterministic voice automation — high-volume, well-defined use cases with full governance.
- Deterministic intent classification
- miniApps® task automation
- Native ASR & Lexis TTS
- Full security & compliance stack
- CCaaS connector ecosystem
- OCP monitoring & analytics
Agentic Voice
Full autonomous platform — Task Agents, zero-shot NLU, self-learning, OCP Knowledge Engine — at one price per resolved call.
- Everything in Conversational Voice
- Autonomous Task Agents + Playbooks
- Zero-shot intent understanding
- OCP Knowledge Engine (RAG) add-on
- Agentic Self-Learning engine
- Developer Co-Pilot access
- Synthetic QA test generation
- Pre-production model quality validation
OCP Bare Metal
On-premise deployment for Tier 1 financial institutions and government agencies with strict data residency mandates.
- Everything in Agentic Voice
- Dedicated bare-metal infrastructure
- Full data sovereignty — zero egress
- Customer-versioned model lifecycle
- FedRAMP-ready configuration
- Executive success partnership
See Agentic Voice resolve
your hardest interactions live.
A platform walkthrough with your own use cases — no slides, no generic demos. Just OCP handling real scenarios.