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ORINEL — AI Data Intelligence Platform

Enterprise data platform: ingest, pipelines, analysis, ML experiments, and AI-powered reports. Turn raw data into AI-driven insights, dashboards, and enterprise reports in minutes.

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SOC2 AlignedRBACAudit LogsEncrypted

Reports

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Pipelines

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Experiments

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Built for the complete data lifecycle

From ingestion to AI-powered reporting. One platform for data engineering, data science, and business analysis.

AI Data Analysis

Run exploratory data analysis, detect patterns and anomalies, and generate ML-ready statistics from your datasets.

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Automated Reports

AI-generated executive summaries, key insights, trend analysis, and business recommendations. Export to PDF, CSV, and PowerPoint.

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Data Pipelines

Extract, transform, and load data from CSV, Excel, PostgreSQL, MySQL, and REST APIs. Background workers for reliable execution.

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Enterprise Security

SOC2-aligned architecture, RBAC, audit logs, and encrypted storage. Rate limiting and secure session handling.

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Enterprise use cases

Built for CTO, Head of Data, and Head of Security. Specific outcomes, not generic claims.

Finance Analytics

Revenue trends, risk indicators, and compliance-ready reporting. Connect to transactional systems and generate executive summaries and audit trails automatically.

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Healthcare Analytics

Patient outcomes, operational KPIs, and regulatory reporting. Secure, role-based access and full audit logs for sensitive data workflows.

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Retail Intelligence

Sales trends, inventory insights, and customer segmentation. Ask business questions, run analysis, and export reports in PDF, CSV, or PowerPoint.

View demo →

Security & compliance

Controls and policies for enterprise and regulated environments. No certification implied unless formally completed and reported.

SOC2 aligned architecture

Controls and practices aligned with SOC 2–type objectives for security, availability, and confidentiality. Certification not claimed unless formally completed.

RBAC

Role-based access control (Admin, Data Engineer, Data Analyst, Data Scientist). Enforced in API and UI. No cross-role or cross-tenant data access.

Audit logs

Login attempts, OTP sent, dataset uploads, pipeline runs, report generation, and report downloads logged with user, organization, timestamp, and IP.

Encrypted storage

Passwords hashed with bcrypt. Sensitive config and credentials referenced via environment variables. Optional encrypted storage for report artifacts.

Security overview →Privacy & data →Compliance →

Start analyzing your data with AI.

Upload datasets, run analysis, and generate enterprise reports in minutes. No credit card required.

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See ORINEL in action

Watch how to upload a dataset, build an AI dashboard, run analysis, and generate reports — in minutes.

Product demo video

Upload dataset → AI dashboard → Analysis → Report generation

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What this platform is

Enterprise AI Reporting Infrastructure that unifies analytics, experiments, and pipelines under one audit trail.

  • Orchestrates analytics pipelines with distributed workers and queue-based execution
  • Enforces workspace isolation — no cross-tenant data access
  • Generates structured reports automatically with version-controlled outputs
  • Maintains audit-grade logs (activity, usage, auth) with export for compliance
  • Supports mapping to SOC 2 control frameworks. Certification not currently claimed. RBAC, RLS, SSO, data retention, audit trail.

Not a generic AI report generator. Not a small SaaS tool. Infrastructure for CTO and Head of Data.

Category spectrum

Traditional BI tools (dashboards, ad-hoc reports) → Point reporting tools (single use case) → Self-built systems (custom scripts, no unified audit) → Orinel: reporting infrastructure (orchestration, isolation, versioning, audit trail). We sit in the last category.

View architecture →

Architecture

Control plane, execution plane, isolation boundary, concurrency safety, audit layer. Technical foundations for controlled execution environments.

Architecture overview

Control plane: Authentication, RBAC at request layer, workspace resolution, job enqueue. All requests validated for identity and role before any resource access.

Execution plane: Report generation and pipeline runs execute in distributed workers. Horizontal scaling worker pool; queue-backed with retry and dead-job cleanup.

Isolation boundary: Workspace isolation enforced at request and storage layer. No cross-workspace data leakage; validated at query and RLS level.

Concurrency safety: Optimistic locking on report and resource updates. Conflict resolution on concurrent edits. Version-controlled outputs; every change traceable.

Audit layer: Activity, usage, and auth logs are immutable and append-only. Export for compliance (CSV/JSON). Correlation IDs for request tracing.

Distributed worker model

Report generation and pipeline runs execute in background workers. Stateless API; horizontal scaling worker pool. No single-point bottleneck.

Horizontal scaling

API and workers scale independently. Queue-backed job processing with retry and dead-job cleanup. Tested with 50+ concurrent report executions.

Concurrency-safe execution

Optimistic locking on report and resource updates. Edit conflicts and race conditions handled. Conflict resolution validated in tests.

RBAC at request layer

Owner, Admin, Editor, Viewer enforced at workspace and resource level before any data access. RLS and application checks. No privilege escalation.

Isolation boundary enforcement

Projects and reports belong to workspaces. No cross-tenant or cross-workspace data access. No cross-workspace data leakage — validated in tests.

Audit logging layer

Activity logs, usage logs, and auth audit logs. Immutable append-only store. Export for compliance (CSV/JSON). Correlation IDs for tracing.

Full architecture overview →

Governed workflows across the data lifecycle

Controlled execution, enforced permissions, version-controlled outputs, audit integrity. Infrastructure-focused — not productivity marketing.

Lifecycle coverage

  • Ingest & connectConnect data sources; workspace-scoped access. No cross-workspace data leakage.
  • Transform & runPipelines and experiments run in distributed workers. Version-controlled outputs; optimistic locking for edit safety.
  • Analyze & reportStructured reports with full audit trail. RBAC at request layer; only authorised roles see outputs.
  • Audit & exportActivity, usage, and auth logs. Immutable; export for compliance. Correlation IDs for tracing.

Security & compliance reporting

Automated, version-controlled reports for internal and external audit. Exportable activity and usage logs. Workspace isolation; RBAC and audit trail support mapping to SOC 2 control frameworks. Certification not currently claimed.

Security overview →

AI experiment documentation

Structured reports for ML experiments and model runs. Version-controlled outputs linked to datasets and parameters. Single audit trail for who ran what, when, and what changed.

Docs →

Analytics pipeline automation

Orchestrate pipelines and report generation in one place. Distributed workers; concurrency-safe; no cross-workspace leakage. One login, one audit trail.

Book demo →

Deployment model

Cloud, optional private cloud / VPC, optional on-premises. Data residency under your control. No vendor lock-in.

Cloud deployment

Standard cloud hosting. Managed infrastructure; automatic updates and scaling. Suitable for most enterprises.

Private cloud / VPC

Deploy inside your VPC. Your network boundaries; data does not leave your chosen region. Optional dedicated workers.

On-premises (optional)

Self-hosted option for air-gapped or strict data residency requirements. Same API and worker model; you operate the stack.

Data residency control

Choose region and storage location. No cross-region replication unless you configure it. Data stays where you specify.

No vendor lock-in

Standard APIs, exportable data, and documented schemas. Audit logs and reports can be exported. No proprietary runtime required to read outputs.

Traditional BI vs point tools vs Orinel

Category spectrum and capability comparison. Orinel is reporting infrastructure, not a point tool.

Category spectrum

  • Traditional BI toolsDashboards and ad-hoc reports; manual assembly; no unified audit.
  • Point reporting toolsSingle use case; no workspace isolation or version control.
  • Self-built systemsCustom scripts; no concurrency control; report sprawl.
  • Orinel (reporting infrastructure)AI-generated structured reports, version-controlled outputs, distributed safe execution, workspace isolation, audit trail. One infrastructure for analytics, experiments, pipelines.
Other approachesOrinel
Manual reporting; spreadsheets and ad-hoc exportsStructured reports with version-controlled outputs and full audit trail
No audit enforcement; who changed what is unclearFull audit trail: activity, usage, auth logs. Export for compliance.
No concurrency control; overwrites and conflictsOptimistic locking; 50+ concurrent report executions tested; no cross-workspace leakage (validated).
Report sprawl; no single source of truthWorkspace isolation; one infrastructure for analytics, experiments, pipelines.

Trust & reliability

Performance evidence, controls, and operational commitment. Engineered for audit visibility.

Performance proof

  • Concurrent execution.Tested with 50+ concurrent report executions. Horizontal scaling worker pool; queue-backed with retry and dead-job cleanup.
  • Edit safety.Optimistic locking for conflict resolution. Version-controlled outputs; every change traceable.
  • Isolation validated.No cross-workspace data leakage — validated in tests. Workspace and tenant isolation enforced at query and RLS level.
Enterprise plans include uptime commitments and dedicated support. Specific terms in contract.

Evidence & controls

  • Architecture diagramDocumented data flow: sources → Orinel (analytics, experiments, pipelines) → reports. Available in docs.
  • Stress testingConcurrent AI jobs and API load tested. Results used to validate horizontal scaling and queue behaviour.
  • Isolation validationWorkspace and tenant isolation verified. No cross-tenant leakage in tests.
  • Load test capabilityDesigned for load testing and monitoring. Health endpoint, structured logging, and observability hooks.
  • Production postureStateless API, immutable audit logs, RLS, rate limiting, secure cookies. Designed for controlled execution environments. Deployment and rollback strategy documented.
Architecture →Security & compliance →
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