Build, Govern, and Scale
your next
AI Agent Fleet.
Operationalize AI across Finance, HCM, SCM, and CX. Saasinator turns Oracle's AI into measurable outcomes faster close, smarter planning, touchless ops.
Agent Framework
Plan → tool use → reflect. Code or low-code; REST-ready.
Vector Search
Unity Catalog–governed embeddings & kNN for RAG.
Model Serving
Unified, OpenAI-compatible API for FM endpoints.
Databricks-Native Use Cases
Accelerate Finance, Ops, CX, and Platform with agents.
Financial Close Agent
NL→SQL for reconciliations, Vector Search for policy citations, drafts journals; approvals logged.
Supply Planning Co-Pilot
Forecast demand, flag exceptions, trigger Lakehouse App workflows with human-in-loop.
Contact Center Insights
Summarize transcripts, detect churn/CSAT drivers, ground responses on SOPs with references.
Talent & Skills Navigator
Infer skills, recommend learning paths, draft role descriptions; governed PII handling.
Modernization Assistant
Document pipelines, generate tests, map lineage; unify runbooks in a Genie space.
AP/AR Automation
Extract, validate, post entries; cite policy KBs; surface exceptions to approvers.
AI Governance
Monitor model performance, track lineage, and ensure compliance with automated documentation.
Customer Service Chatbot
Provide instant support, answer FAQs, and escalate complex queries to human agents.
Supply Chain Analytics
Analyze supply chain data, identify bottlenecks, and optimize logistics.
Employee Onboarding Assistant
Guide new hires through the onboarding process, answer questions, and provide resources.
Engineer's Build Lifecycle
From prototype → agent → app → API, with evals & observability.
Define
Scope intents, data, guardrails.
Choose models, tools, vector indexes.
Design
Author agents (no-code or Python).
Configure Vector Search & FM endpoints.
Evaluate
Run eval sets (quality/cost/latency).
Add guardrails, refine prompts/tools.
Deploy
Serve REST APIs, embed in
Apps/Genie, monitor with
observability.
Security, Trust & Governance
Unity Catalog First
Fine-grained access, lineage, and policy inheritance across agents, vectors, and apps.
Audit & Observability
Trace tools, SQL, retrievals, and model calls; evaluate QoS and control spend.
Guardrails
Tool allowlists, rate/credit limits, human approvals for sensitive actions.
Build high-quality agent systems
Transform your data effortlessly
Prepare data with seamless integration for GenAI and ML workflows
Databricks empowers you to ingest any data type and orchestrate jobs to prepare it for your GenAI or ML applications. With built-in governance, it simplifies data featurization and creates vector indexes for RAG using Mosaic AI Vector Search, unifying data and model pipelines to streamline workflows and cut costs.
See Vector Search →
Saasinator for Databricks
Platform engineering, orchestration, and enablement—optimized for Mosaic AI Agent Framework, Vector Search, and Model Serving.
Blueprint & Readiness
Use-case triage, ROI/credit models, UC policies, vector schema, and eval design.
Build & Orchestrate
Agents, tools, Vector Search, FM Serving, Genie spaces, and Lakehouse Apps.
Operate & Upskill
Observability (quality/cost), guardrails, SDLC playbooks, and enablement workshops.
Pilot in Weeks—With Governance
Architecture workshop, UC policy setup, vector indexing, agent config, evals & guardrails, Lakehouse App & API.