Sigmoid helps enterprises achieve autonomous, always-on systems with AI embedded into workflows. Unified agentic AIOps, MLOps, and DataOps drive faster issue remediation, proactive optimization, and high-performance operations.
AI-driven operations for the modern enterprise
Unified AI Operations
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Connect systems, data, and workflows in one intelligent workspace for complete visibility and control.
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Context-aware automation ensures decisions are informed, accurate, and traceable across teams.
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Eliminate operational silos through integrated monitoring, collaboration, and reporting.
Proactive Detection and Resolution
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AI-powered monitoring predicts and prevents incidents before they impact performance.
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Automated correlation across logs, metrics, and events accelerates RCA and response time.
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Reduce Mean Time to Resolution (MTTR) by up to 70% through self-healing pipelines and automated remediation.
Agentic Automation
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Autonomous AI agents execute runbooks, resolve repetitive issues, and trigger workflow automation.
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Intelligent routing prioritizes critical events and minimizes manual intervention.
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Learn-and-adapt systems improve accuracy over time, driving low-touch, no-touch operations.
Human-AI Collaboration
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AI delivers recommendations, summaries, and next-best actions directly within collaboration tools.
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Empower teams to focus on innovation while AI handles the repetitive and routine.
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Maintain transparency and control with human oversight on automated decisions.
Continuous Optimization and Governance
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Continuous performance tuning through data-driven insights and predictive analytics.
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Embedded Responsible AI ensures fairness, transparency, and compliance across workflows.
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Adaptive cost guardrails optimize infrastructure spend while maintaining uptime and agility.
AI automation across the operational lifecycle
DevOps: Intelligent release automation
AI-driven CI/CD pipelines and automated infrastructure management enable faster, more predictable deployments. Intelligent orchestration reduces manual effort, minimizes release failures, and keeps critical systems continuously updated and stable.
DataOps: Trusted data operations
Automated ingestion, quality checks, and lineage monitoring ensure data stays clean, governed, and production-ready. AI-powered observability proactively detects anomalies and bottlenecks, enabling reliable data flows that support real-time analytics and AI workloads.
MLOps: Autonomous model performance management
Continuous monitoring, drift detection, and automated retraining keep models accurate, explainable, and compliant. AI-led governance and performance checks ensure ML systems operate reliably at scale without manual oversight.
LLMOps: Governed and efficient GenAI operations
Automated prompt management, model oversight, and environment governance streamline GenAI workflows. Intelligent guardrails manage cost, compliance, and quality, enabling safe, scalable deployment of large language models across the enterprise.
Why choose Sigmoid?
Intelligent automation across operations
We design AI-driven workflows that elevate operational reliability by automating detection, correlation, and resolution, enabling consistent performance with reduced manual effort.
Integrated service experience
We streamline how teams work by connecting tools, data, and processes into a single operational flow so issues are resolved faster and experiences stay consistent end-to-end.
Unified visibility for faster decisions
We unify context from all infrastructure systems, applications, data platforms, and collaboration tools that gives giving teams the clarity they need to diagnose issues quickly and act on time.
Built-in oversight and control
We embed governance, auditability, and policy controls directly into automated workflows so teams can scale AI safely while maintaining trust, security, and compliance.
Accelerators for AI Managed Services
Sigmoid AIOps
This accelerator is built to operationalize AI-driven automation at scale by combining observability, intelligent correlation, and automated remediation. It helps streamline complex IT and data ecosystems for uninterrupted performance and measurable efficiency gains, driving reduced operational overhead and lower support costs.
Key capabilities:
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Real-time anomaly detection and automated root cause analysis
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Multi-agent framework for triage, resolution, and workflow automation
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Unified correlation and diagnosis of incidents across Azure, AWS, Snowflake, SAP, Salesforce, Databricks, Git, ServiceNow, JIRA, MS Teams, MS Copilot, Collibra, Informatica IICS etc.
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Policy-driven remediation and predictive cost optimization
Sigmoid RAPID
This accelerator helps enterprises scale Generative AI safely and efficiently with governance, cost visibility, and compliance built in. It unifies AI development, deployment, and oversight into a single control framework for secure, transparent, and accountable operations.
Key capabilities:
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Single-pane governance with built-in RBAC, audit trails, and chargeback
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30+ vetted models through a secure LLM Garden for controlled experimentation
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Reusable templates, prompt libraries, and monitored environments for faster rollout
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Unified collaboration across business, operations, and security teams
Success stories
faster issue resolution through Agentic AIOps enabling predictive, scalable and cost-efficient data operations for a global F500 consumer goods company.
reduction in operations cost through continuous data-pipeline availability, real-time ingestion and automated monitoring of cloud operations at a global enterprise.
Featured insights
WHITEPAPER
MLOps best practices to solve AI/ML production hurdles
INFOGRAPHIC
DevOps vs. DataOps
DATA LENS