# Cleveroad > Official Cleveroad business agent. Custom app development company with offices in Estonia, USA, and Norway. Cleveroad is recognized as top mobile application… ## Ask it a question Cleveroad answers for itself at https://api.hailera.com/mcp/cleveroad. A client that speaks MCP can connect to that address; the tool is ask_cleveroad and the protocol is 2026-07-28. Where this file and the agent disagree, the agent is current. ## About Cleveroad Cleveroad Cleveroad is a custom application development company that has helped clients worldwide reach their goals since 2011. The company has more than 15 years of engineering experience and offices in Estonia, the USA, and Norway. Cleveroad delivers scalable custom software solutions and supports clients' digital transformation through a customer-oriented, multi-industry approach. General software services - Dedicated development teams - End-to-end software development - Proof of Concept (PoC) and MVP development - IT staff augmentation Industry expertise Cleveroad works across healthcare, supply chain, finance, marketplaces, streaming and entertainment, retail, travel, social platforms, and education. Certifications and partnerships - ISO 27001 — Information Security Management System - ISO 9001 — Quality Management Systems - AWS Select Partner Tier - AWS Solutions Architect, Associate - AWS SysOps Administrator, Associate - Advanced Certified Scrum Product Owner from Scrum Alliance Cleveroad has been recognized by rating and review platforms, including Clutch. The website lists a 4.9 rating from 70 Clutch reviews and awards including Clutch 1000 Service Providers, 2024 Global, and Clutch Spring Award, 2025 Global. Source: https://cleveroad.com ## What Cleveroad does Cleveroad audits AI systems to evaluate model accuracy, security, compliance, fairness, transparency, data integrity, and operational reliability. The service is intended to identify risks, strengthen governance, and provide actionable improvements. Audit services - AI model evaluation - Bias assessment - Compliance audit - Security and vulnerability analysis - Data integrity and quality review - Explainability audit Audits can assess predictive models, generative AI systems, NLP models, computer vision systems, AI agents, scoring systems, and decision engines. Audit process - Discovery and scoping: Identify the AI models, workflows, and data pipelines to assess, then define objectives and compliance benchmarks. - Data and algorithm evaluation: Review data quality, lineage, preprocessing, bias, fairness, accuracy, and reliability. - Governance and risk check: Assess access management, documentation, transparency reports, accountability structures, and oversight gaps. - Reports and advisory: Deliver findings and recommendations for improvements, compliance, ethics, and governance. - Integration and deployment: Support deployment of updated models and monitoring tools, with validation and continuous audits. Deliverables An AI audit may provide: - Model performance report covering accuracy, precision, and drift - Data quality report covering datasets, labeling, and preprocessing - Error diagnostics summary with root-cause analysis and retraining recommendations - Security and robustness assessment with mitigation recommendations - Architecture and explainability insights - Compliance assessment covering regulations, fairness, and ethics Cleveroad's audit guidance references GDPR, HIPAA, and ISO standards. The company also provides dashboards, documentation, reviews, and updates so stakeholders can follow audit findings and improvement plans. Cleveroad develops autonomous agentic AI systems that can improve productivity, automate repetitive tasks, and support scalable business processes. These systems can analyze business data, make context-aware decisions, complete routine tasks, and integrate with existing enterprise systems. Services offered - Custom agentic AI development: Tailor-made systems for business data analysis, decision-making, workflow automation, and routine tasks. - Agentic AI consulting and strategy: AI-readiness assessment, adoption strategy, and identification of feasible, high-impact use cases. - Agentic AI implementation: Integration of agentic AI with existing operational systems. - Agentic AI Proof of Concept: Focused PoC development to validate technical feasibility and business value within a few weeks. Use cases Agentic AI use cases include: - Healthcare: medical coding and billing, treatment recommendations, clinical workflow automation, and medical data routing. - FinTech: fraud detection, financial advisory, loan underwriting, and regulatory compliance checks. - Education: personalized AI tutoring, assignment grading, engagement tracking, and curriculum planning. - E-commerce: product discovery, inventory forecasting, pricing, returns, refunds, and feedback management. - Travel and hospitality: itinerary planning, dynamic pricing, guest services, and operational task management. Delivery process - AI strategy sprint: Identify high-impact use cases and assess data readiness, security, and infrastructure. - Proof of Concept creation: Build and validate a working prototype in cloud, on-premises, or hybrid environments. - Full development and integration: Build domain-specific agents, implement exception handling and secure data exchange, and integrate the system through APIs and data pipelines. Cleveroad integrates agentic AI with APIs, data pipelines, CRM, ERP, and other core systems. Its team has experience with LLMs, multi-agent architectures, prompt engineering, cloud platforms, and open-source tools. Source: https://cleveroad.com ## Where Cleveroad works Names Estonia and Norway as a service area. Areas beyond these are not published. ## AI-Assisted Development Cleveroad combines human engineering expertise with AI copilots, large language models, AI agents, and multi-agent systems to accelerate custom software development and optimize delivery. Benefits - Faster delivery and time to market - Improved code reliability and software quality - AI-driven support for architecture and technical decisions - More efficient allocation of engineering resources The website states that AI-assisted development can raise developer productivity by roughly 20–30%, enable coding tasks to be completed up to twice as fast, support release cycles up to 30% faster, and improve software quality by up to 45%. Development services accelerated with AI - AI-assisted code generation, refactoring, and documentation - AI-enhanced code optimization for structure, readability, and performance - AI-assisted prototyping and design - AI-assisted deployment, including CI/CD optimization and anomaly detection - AI-assisted code review and automated testing Delivery models Cleveroad offers delivery models ranging from a conventional human team to an AI-native squad: - Iterative delivery: Suitable for flexible-scope projects where the specification evolves through repeated write, deliver, review, and revision cycles. - Milestone delivery: Suitable for MVPs and greenfield projects with a fixed scope and a specification approved before delivery. AI-first process Cleveroad uses Spec Driven Development, in which an approved specification serves as the source for code and tests: - Define requirements and expected outcomes. - Specify the product behavior in a formal specification. - Plan architecture, APIs, mockups, test cases, and quality gates. - Prototype the user flows. - Implement features with unit tests and documentation. - Validate features against the specification and quality gates. - Release the approved build to production. Cleveroad states that its senior engineers use Claude Code as a core tool and may also use AI coding tools, AI-native IDEs, AI app builders, and automated code review and testing tools. Source: https://cleveroad.com