Data Readiness
Before connecting AI to your enterprise data, discover sensitive information, map PII exposure, and define secure access controls.
Workflow Value
Deploying an enterprise retrieval workflow system or connecting an LLM to your internal file shares (SharePoint, S3) without knowing what's inside them can lead to massive data leakage, privilege escalation, and compliance failures.
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. Your data is scanned in memory and never leaves your environment.
Basic regex scanners produce massive false positives. We use a 3-tier approach: Pattern matching, NLP-based Named Entity Recognition (NER), and Exact Data Match. It reads column headers and surrounding sentences to accurately identify SSNs, financials, and IP.
We generate board-ready reports highlighting specific exposure vectors, mapping data lineage (how sensitive data moves between systems), and providing strict access-control recommendations before AI integration.
Agent Workflow Architecture
Every solution is implemented as a controlled workflow, not a loose chatbot. The agent operates inside approved data 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 (in-place scanning) so your data never leaves your infrastructure.
Bring the workpaper, evidence review, or diligence process that consumes the most hours. We will map a practical AI-assisted pilot around your methodology.