Case Study
AI-Enhanced Internal Search for Poland's Largest Bank
Softwise.AI built an AI-enhanced search engine for PKO Bank Polski (PKO BP) - Poland's largest bank - delivering precision access to the bank's internal knowledge repositories. The platform unified disparate information sources through comprehensive data standardization and ran fully on-premise, with tailored integration into the bank's existing infrastructure and security perimeter.
CLIENT
PKO BP
YEAR
2022
INDUSTIRES
Banking - Internal Knowledge & Search
DELIVERABLES
AI-Enhanced Search Engine, Comprehensive Cross-Source Data Standardization, Secure On-Premise Deployment
The problem
PKO BP's employees needed fast, precise access to knowledge spread across many internal repositories - each with its own format, schema, and update rhythm. Off-the-shelf SaaS search was not an option: the bank operates under strict regulatory and security requirements that ruled out external hosting of internal data. The bank needed a search experience that matched modern AI tools, but built and deployed entirely within its own infrastructure.
{Key Challenges}
Why Poland's largest bank couldn't deploy SaaS search across its internal knowledge?
Disparate sources, inconsistent formats.
Knowledge lived across multiple repositories built and maintained by different teams over years, with no unified schema.
Regulatory and security constraints.
Banking data could not leave the bank's perimeter - any solution had to run on-premise and integrate with existing controls.
Precision over recall.
Employees needed the right answer, not a long list of candidates - the cost of an imprecise result in a banking workflow is higher than in a consumer setting.
Integration with existing infrastructure.
The search engine had to plug into the bank's existing systems, not replace them.
{Process}
How we delivered an on-premise AI search engine in 4 stages?
1. Discovery of internal repositories
Softwise.AI mapped the bank's internal knowledge estate - identifying the repositories, formats, and access patterns that needed to feed into a unified search experience.
2. Data standardization design
A comprehensive standardization layer was designed to bring disparate information sources into a coherent, queryable format - the foundation on which the AI search could work.
3. AI-enhanced search engine build
The search engine was built to deliver precision retrieval across the standardized knowledge base - tuned for the relevance and confidence requirements of internal banking workflows.
4. Secure on-premise deployment
The system was deployed fully on-premise, with tailored integration into the bank's existing infrastructure - meeting the security, access-control, and audit requirements of a tier-one financial institution.
Solution
AI-enhanced search engine
A precision-tuned internal search engine giving bank employees fast, relevant access to the right document across many repositories - in one query.
Comprehensive data standardization
A unification layer bringing disparate internal sources into a consistent format - making integrated, cross-repository search possible without forcing a single content owner to change anything.
Secure on-premise deployment
A deployment architecture built around the bank's own infrastructure and security perimeter - with tailored integration into existing systems rather than a parallel stack.
{Results}
A precision-focused internal search engine delivering unified access across previously siloed knowledge repositories.
A standardized data foundation spanning multiple internal sources with different formats and schemas.
A fully on-premise deployment integrated with the bank's existing infrastructure and security controls.
A reusable architecture for further AI deployments inside the bank's perimeter.
{Business impact}
Faster, more accurate internal answers. Employees found the right information without navigating multiple systems manually.
Security posture preserved. On-premise deployment kept sensitive banking data fully inside the bank's perimeter.
Cross-team knowledge unlocked. Information silos created by historical tool choices became searchable as one estate.
A foundation for further AI work. The standardized data layer and on-premise architecture became reusable infrastructure, not a one-off project.
{Key recommendations}
Standardize data before adding intelligence. AI search is only as good as the consistency of the sources behind it.
Deploy where the data lives. For regulated institutions, on-premise is a design choice, not a fallback.
Optimize for precision in internal search. Banking workflows reward the right answer, not the long list.
Treat the unification layer as reusable infrastructure, not project plumbing.
SUMMARY
Softwise.AI delivered an AI-enhanced internal search engine for PKO BP, unifying disparate knowledge repositories through comprehensive data standardization and deploying fully on-premise with tailored integration into the bank's existing infrastructure - giving Poland's largest bank a precision search experience inside its own security perimeter.