Data Readiness
Before connecting AI to your enterprise data, discover sensitive information, map PII exposure, and define secure access controls.
Workflow Value
Before a model touches SharePoint, S3, databases, or file shares, teams need to know where sensitive data sits, who can access it, which repositories are over-permissioned, and what should be masked or excluded.
We deploy Pelestra, our data readiness engine, directly into your infrastructure via Docker. It connects to PostgreSQL, S3, Azure Blob, and file shares via read-only APIs so source data can be scanned in place inside the approved environment.
Basic regex scanners create noisy findings. We use a 3-tier approach: pattern matching, NLP-based named entity recognition, and exact data match. It reads column headers and surrounding context to improve classification of SSNs, financial data, and sensitive IP.
The output is a practical readiness map: sensitive repositories, likely exposure paths, lineage notes, access-control recommendations, masking needs, and which workflows are safe to test first.
Workflow Architecture
Every solution is implemented as a controlled workflow, not a loose chatbot. The system operates inside approved data and tool scopes, produces inspectable outputs, and routes judgment back to the right human owner.
Define the exact workflow, input sources, business rules, user roles, output format, and what the AI agent is allowed to do.
Pull only approved documents, records, ERP context, control libraries, or playbooks before the agent drafts or acts.
Generate findings, matrices, notes, SQL-backed answers, or queues with source references, exception reasons, and confidence signals.
Measure reviewer edits, pass/partial/fail outcomes, time saved, exception quality, and adoption before moving to adjacent workflows.
FAQ
It is a systematic evaluation of your enterprise data to identify sensitive information, assess current access controls, and determine what data is safe to expose to AI models.
No. We deploy scanning tools within your environment for in-place scanning so source data can remain inside your infrastructure.
Bring the workpaper, evidence review, diligence process, ERP answer queue, or reporting loop that consumes the most hours. We will map a practical workflow around your methodology.