Harnessing autonomous agents and high-fidelity data architectures to drive enterprise transformation. We bridge the gap between legacy infrastructure and intelligent automation.
Defined roadmaps for scaling intelligence.
Strategic planning for seamless AI integration into existing workflows and future-proofing your tech stack.
Methodical scaling of AI capabilities across departments, ensuring cultural alignment and technical readiness.
Realizing tangible business value through end-to-end intelligent automation and process re-engineering.
Get client-ready shortlists in minutes
AiMe is our proprietary AI agent-based recruitment system designed to automate sourcing, normalization, and archival. It exponentially increases recruiter efficiency and time-to-hire by delivering a standardized, pre-filtered candidate shortlist that has passed background verification.
Born from the friction of AI talent scarcity and deployment complexity, AiMe was built to accelerate transformation while minimizing human-capital bottlenecks.
Driving immediate bottom-line impact by reducing time-to-market for AI initiatives by up to 60% while ensuring 99.9% data compliance.
Precision performance engineered for the modern enterprise.
Accelerate recruitment cycles through AI-vetting.
Precision matching of candidate skills to AI needs.
Automated adherence to regional data laws.
Ensuring high-integrity inputs for every model.
Drop in the role requirements as PDF or text. AiMe reads and extracts the key skills, level, and must-haves.
Three fit tiers in one go: Exact (100%), Strong (80%), and High-potential (60%) candidates so coverage and quality stay balanced.
Searches DCV's internal CV bank and country-relevant job boards in a single workflow — no extra logins or tabs.
CVs are auto-formatted into DCV's template and filed by Vacancy → Fit level → Source, ready to send to the client.
Case Studies
Transforming Insurance with Agentic AI & Managed Testing built on DCV's GenAI OS Reference Architecture and Mitig8 Test Platform
DCV deployed reusable AI agents tailored to specific insurance business logic.
The project involved accelerating the 24/7 claims resolution process by deploying agents that autonomously extract structured data from customer-uploaded damage images and process routine inquiries. We utilized foundational LLMs to generate synthetic "loss run" scenarios, enabling dynamic premium optimization against climate-driven catastrophes.
The insurance landscape is driven by consolidation and integrating massive legacy systems requires flawless delivery.
Our Mitig8 Agentic Test Platform acts as an autonomous software testing team, automatically generating strategies, scenarios, and traceability reports directly from client project repositories. The value it brings is that it reduces test preparation costs by 60% while ensuring zero disruption to customer service during multi-billion-pound acquisitions.
DCV created continuous-monitoring agents which scan tech portfolios to evaluate the rapidly shifting risk landscape of generative AI and Web3. This helps to instantly evaluate third-party claims related to AI hallucinations, model errors, and IP infringement to provide underwriters with real-time risk scores.
