Claritas One
Data & AI/Virtual Assistants

Enterprise AI Chatbots & Virtual Assistants

We build large language model-powered virtual assistants that handle complex enterprise interactions with the accuracy, compliance, and audit trail that regulated industries require. From internal knowledge management to customer-facing service automation, our conversational AI delivers measurable deflection rates and CSAT improvements from day one.

AI
NL
KB
ML

92% resolution rate · <2s avg response time

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Your knowledge base, conversational.

assistant.yourcompany.com

What is our refund policy for enterprise contracts?

Based on the Enterprise Master Services Agreement (v4.2), enterprise contracts include a 30-day satisfaction guarantee. After the initial period, refunds are prorated based on remaining contract term, minus any consumed professional services hours. A formal request must be submitted through the account management portal.

Enterprise MSA v4.2, Section 8.3

Does that apply to annual and multi-year agreements differently?

Yes. Annual agreements follow the standard proration schedule outlined above. Multi-year agreements (24+ months) include an early termination fee of 15% of remaining contract value, as stipulated in the Long-Term Agreement Addendum. However, customers in the first 90 days of a multi-year term can invoke the Extended Evaluation Clause for a full refund.

LTA Addendum, Clause 3.1; Evaluation Policy Rev.7
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Our Approach

From raw knowledge to intelligent conversation.

Phase 01

Conversational AI Strategy & Use Case Scoping

We assess your highest-volume interaction patterns — support tickets, internal helpdesk queries, sales qualification, HR policy questions — and quantify the deflection rate and cost savings achievable through automation. Use case prioritisation is based on interaction volume, answer determinism, and regulatory sensitivity.

Phase 02

Knowledge Architecture & RAG Implementation

We design and implement a Retrieval-Augmented Generation pipeline that ingests your structured and unstructured knowledge sources — policy documents, product documentation, CRM data, ticketing history — with chunking strategies, embedding models, and retrieval algorithms optimised for your content type.

Phase 03

LLM Selection, Fine-Tuning & Guardrail Engineering

We select the appropriate foundation model — GPT-4o, Claude, Llama, or a domain-specific model — and implement system-level guardrails, output validation, and adversarial prompt defences. For regulated industries, we implement citation enforcement and answer confidence thresholding to prevent hallucinated responses.

Phase 04

Multi-Channel Deployment & Integration

Assistants are deployed across your required channels — web widget, Microsoft Teams, Slack, WhatsApp, or native mobile — with session state management, authenticated user context injection, and CRM integration that gives the assistant access to customer history without requiring manual lookup.

Phase 05

Governance, Compliance Logging & Continuous Improvement

Every conversation is logged to a tamper-evident audit store with full retrieval context, model version, and response metadata. Human review workflows flag low-confidence responses for QA review, and monthly model fine-tuning cycles use reviewed interactions to improve answer quality continuously.

Compliance-grade accuracy with the conversational fluency your teams and customers expect.

Every response is grounded in your verified documents, with full source citation and audit trails for regulated industries.

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The intelligence layer

Enterprise conversational AI deployments fail most often not due to model limitations, but due to poor retrieval architecture, inadequate guardrails, and the absence of a governance framework that satisfies compliance and legal review. Organisations in financial services, healthcare, and professional services cannot deploy LLMs that hallucinate answers to policy questions or retrieve information from unvetted sources. Our conversational AI engineering practice builds grounded, governed, and auditable assistants — where every response is traceable to a source document, every conversation is logged for compliance review, and the model refuses to answer outside its defined knowledge boundaries with a graceful, professional handoff.

Capabilities

Everything your AI assistant delivers.

Retrieval-Augmented Generation (RAG) with enterprise knowledge base integration
LLM fine-tuning and domain adaptation for specialist vocabulary and compliance
Guardrail engineering: hallucination prevention, citation enforcement, and refusal handling
Multi-channel deployment: web, Teams, Slack, WhatsApp, and native mobile SDK
Authenticated user context injection with CRM and ticketing system integration
Tamper-evident conversation audit logging for compliance and regulatory review
Human-in-the-loop escalation with intelligent routing and case creation
Conversation analytics: deflection rate, CSAT, containment, and gap analysis

Use Cases

Enterprise use cases for conversational AI

Customer Support Deflection

Automate 60-70% of L1 support interactions

Internal Knowledge Base

Instant answers from company policies and documentation

Sales Qualification

AI-powered lead scoring and initial qualification conversations

HR & IT Helpdesk

Employee self-service for common HR and IT requests

Compliance Q&A

Governed answers to regulatory and policy questions

Onboarding Assistant

Guide new customers through product setup and activation

Security & Governance

Built for trust and accountability

Audit Trail

Every conversation logged to tamper-evident store with full retrieval context

Guardrails

Hallucination prevention, citation enforcement, and refusal handling

Compliance

SOC 2, GDPR, and HIPAA-ready architecture with consent management

Deploy Conversational AI Your Compliance Team Will Approve

Our conversational AI architects will assess your interaction volume, knowledge architecture, and compliance requirements to design a governed virtual assistant strategy.

Deploy Your AI Assistant