Viacheslav Kostin
CEO WislaCode Solution
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Automotive Analytics and BI Solutions
We partner with OEMs, dealers, captives, mobility operators and service networks to design and implement bespoke analytics and BI – built for real‑time visibility, forward‑looking insight and action. Our focus is custom engineering and integration within your environment, not a boxed product.
Automotive analytics system development
We create strong analytics platforms. They combine operational data, process it well, and show insights for specific roles through easy-to-use dashboards and reports. The result is practical, data-driven decision-making. It helps spot inefficiencies, track trends, and act quickly in sales, aftersales, and fleet operations.
Custom BI applications and insight platforms: We design role‑based BI apps for dealers, captives and mobility providers. You can expect model-mix and margin views, VHC conversion tracking, and technician productivity. Also, finance-penetration and stock-turn dashboards will be updated in near real time. You can drill down to vehicle, site, and advisor levels.
Operational analytics and performance visibility: From showroom to workshop, we instrument the KPIs that matter: enquiry‑to‑sale, test‑drive conversion, overage stock, days‑to‑turn, parts fill rate and CSI trends. Interactive scorecards surface leakage, seasonality and exceptions so leaders can intervene early.
Applied AI and machine learning: We deliver demand forecasting, pricing optimisation, lead scoring, churn risk, anomaly detection and service‑capacity modelling. Models are monitored for drift and bias, with explainability so commercial teams trust and adopt recommendations.
Modernising legacy data estates: We refactor ageing warehouses and reporting stacks, moving from spreadsheets and siloed DMS extracts to a governed lakehouse. You get improved data quality, better lineage, and master data for vehicles and customers. Plus, you enjoy faster refresh cycles that won’t disrupt daily operations.
Secure API and data integration: We connect DMS, CRM, OEM feeds, pricing engines, telematics, marketplace listings and finance systems. The integration layer standardises schemas, removes duplicates, and enforces access controls. This keeps downstream analytics consistent and reliable.
Enterprise systems integration: End‑to‑end orchestration across dealer networks and partners: identity, authorisation, event streaming and change‑data‑capture pipelines. Data moves smoothly between sales, service, finance, and inventory systems. This helps in making timely decisions.
Comprehensive analytics and BI features
- behaviour analysis and buying‑pattern discovery
- journey mapping and interaction optimisation
- audience segmentation for targeted marketing
- loyalty and retention evaluation
- customer lifetime value modelling
- real‑time fleet and vehicle performance
- inventory tracking and optimisation
- dealership and supplier efficiency assessments
- diagnostics and predictive maintenance
- equipment utilisation and fuel‑efficiency insights
- quality control analysis and regulatory compliance views
At WislaCode, we start by understanding your unique business needs. Our planning makes sure the automotive analytics and BI solutions match your goals and go beyond your expectations.
Planning
Analysis
We prioritise quality through extensive testing, covering functionality, usability, performance, and security. This ensures our automotive analytics systems are reliable, efficient, and secure for your operations.
Testing
UX Research
Our scalable solutions use microservices architecture. They grow with your business and offer a flexible, future-proof IT landscape.
Design
Development
From development to deployment, we guarantee a seamless launch and long‑term operational stability for your analytics platform.
Launch
Support
Case: from manual leasing to a data‑driven platform
A leasing provider asked us to digitise manual workflows. They want to gain operational insights in sales and aftersales.
We delivered a self‑service customer portal, a dealer area and deep integrations for applications, contracts, invoicing and document management. Built with Java, Spring, JavaScript and React, the first release shipped in six months. Routine interactions became automated.
As a result, staff workload dropped by 68%. Also, analytics revealed funnel performance, approval cycles, and revenue leakage. This was a bespoke implementation within the client’s estate, not an off‑the‑shelf product.
Why WislaCode?
Hands‑on experience with dealership operations, captives and mobility products. We translate showroom realities and workshop constraints into meaningful KPIs – not vanity metrics.
Proven delivery
Deep expertise stitching together DMS/CRM, OEM data, finance systems and marketplaces. Clean, resilient pipelines keep dashboards accurate and timely – even at peak loads.
Integration first
Pragmatic data‑quality rules, lineage and MDM with lightweight processes. The outcome: trusted dashboards, faster refreshes and fewer ad‑hoc spreadsheets.
Data governance
Forecasts and pricing recommendations arrive with rationale and guardrails. Commercial teams get actions, not opaque scores, and models are monitored post go‑live for drift and bias.
Using AI
FAQ About Analytics and BI Solutions Development
Most programmes aim to increase sales velocity, reduce overage stock and improve aftersales margins. Typical gains include better enquiry‑to‑sale conversion, tighter days‑to‑turn, higher finance and add‑on penetration, and improved technician efficiency. You should also see fewer manual reports, faster month‑end, and clearer accountability by site, team and channel. We baseline KPIs early, then deliver in short increments so value appears within weeks, not months, while maintaining data quality and governance.
We start with a connectivity audit, mapping authoritative sources for vehicles, customers, stock and transactions. Where APIs exist, we use secure, rate‑aware connectors; otherwise, we implement CDC or scheduled extracts with validation and deduplication. A canonical data model standardises entities across vendors. Lineage, access controls and error handling are built into the pipelines, so downstream dashboards and machine learning stay consistent and auditable.
Yes. We catalogue critical spreadsheets, reverse‑engineer logic, then replace them with governed datasets and parameterised reports. During transition, we run both paths in parallel to reconcile results and build trust. Users keep familiar filters and views, but gain version control, refresh schedules and role‑based access. This approach reduces key‑person risk, eliminates conflicting numbers, and shortens the time from data refresh to decision.
Quick wins typically include lead scoring to prioritise follow‑up, demand forecasting to guide ordering and transfers, and price elasticity models for used stock. In aftersales, capacity forecasting and no‑show prediction stabilise workshop loading. We pair models with clear actions – contact cadence, pricing bands, transfer suggestions – so teams can act immediately. Each model is monitored for drift and fairness, with human override where appropriate.
We implement validation at ingestion, schema enforcement, and business rule checks for KPIs. Data quality metrics – completeness, freshness, duplication, are tracked and surfaced in the BI layer. Every metric has documented definitions and lineage from source to visual, so finance and operations reconcile to the same number. Alerts flag anomalies or late data, preventing decisions on stale or partial information.
We usually target a first slice of value within four to six weeks: high‑impact dashboards and a stable data pipeline for a priority domain, such as sales funnel or used‑car stock. Delivery is iterative, with fortnightly demos, shared backlogs and clear acceptance criteria. As trust builds, we add domains – aftersales, parts, finance and introduce ML where it brings tangible benefit. Knowledge transfer and documentation are continuous to embed capability in your teams.
Viacheslav Kostin, CEO
20+ years of experience in managerial positions in IT and banking.
Viacheslav Kostin, CEO
Previous roles: CEO in IT, Director of Strategy and Marketing in Banking, Curator of Holding Banks, Head of Products and Project Office.
Education: MBA for Executives at IMD (Switzerland), Leading Digital Business Transformation (IMD). Provides consulting in strategy and digital transformation.
Vasil Pahomov, CTO
20+ years of experience as a developer, analyst, and solutions architect.
Vasil Pahomov, CTO
Designs resilient, high-load systems with multiple integrations for banks and financial institutions. Expertise in distributed storage and microservices architecture.