--- title: Media algorithm governance decision infrastructure description: Context OS delivers media algorithm governance decision infrastructure for moderation, ad placement, and recommendation accountability. image: https://www.elixirdata.co/hubfs/Xenon%20Daily%20Work-1%20-%202026-04-23T163953.873.png --- ![campaign-icon](https://assets.elixirdata.co/assets/campaign.svg) The Context OS for Agentic Intelligence [![elixir-logo](https://www.elixirdata.co/hubfs/elixirdata-logo.svg)](https://www.elixirdata.co/) - Platform - [Context OS](https://www.elixirdata.co/platform/context-os/) - [Unify Data](https://www.elixirdata.co/platform/unify-data/) - [Business Context](https://www.elixirdata.co/platform/business-context/) - [Decision Infrastructure](https://www.elixirdata.co/platform/decision-infrastructure/) - [Build Agents](https://www.elixirdata.co/platform/build-agents/) - [Governed Agentic Actions](https://www.elixirdata.co/platform/governed-actions/) - [Decision Traces](https://www.elixirdata.co/platform/decisiontraces/) Platform The Decision Harness for Enterprise AI. Three primitives. One dual-gate architecture. Every agent action compiled, governed, and recorded with full lineage. [Explore Context OS →](https://www.elixirdata.co/platform/context-os/) The Three Primitives [⊞ Context Layer Decision-grade context compiled at the moment of decision](https://www.elixirdata.co/platform/context-os/) [⊛ Governance Layer Dual-gate policy enforcement — before reasoning, before execution](https://www.elixirdata.co/platform/decision-infrastructure/) [◈ Memory Layer Full-lineage Decision Traces, never summarized, never compressed](https://www.elixirdata.co/platform/decisiontraces/) [⟳ Feedback Band Closed-loop feedback and continuous improvement across all three layers](https://www.elixirdata.co/platform/business-context/) Agentic Execution [◉ Build Agents Design and deploy governed agents on Context OS](https://www.elixirdata.co/platform/build-agents/) [▤ Dual-Gate Architecture How every action flows through Gate 1 and Gate 2](https://www.elixirdata.co/platform/governed-actions/) [▦ Decision Traces Live audit record for every agent decision, audit-ready by default](https://www.elixirdata.co/platform/decisiontraces/) [↗ Trust Graduation Shadow → Supervised → Bounded → Full Autonomy](https://www.elixirdata.co/platform/unify-data/) **Generic harnesses plateau.** Context OS compounds. 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Find Context OS by the role you own or the industry you operate in. Every solution anchored to the same Decision Harness — governed context, dual-gate enforcement, full-lineage traces. [View all solutions →](https://www.elixirdata.co/solutions/operations-sre/) By Role [⚖ Risk & Compliance Continuous risk governance with audit-ready Decision Traces](https://www.elixirdata.co/solutions/governance-risk-compliance/) [🛡 Security & SOC Governed threat detection and response with human-in-the-loop authority](https://www.elixirdata.co/solutions/security-and-soc/) [⚡ Operations & SRE Incident response grounded in validated context, every action traced](https://www.elixirdata.co/solutions/operations-sre/) [$ Finance & Procurement Approvals, thresholds, and spend controls enforced before execution](https://www.elixirdata.co/solutions/finance-and-procurement/) By Industry [🏦 Financial Services Model risk management, trading controls, regulatory defensibility](https://www.elixirdata.co/industries/banking-and-financial-services/) [⚕ Healthcare & Life Sciences Clinical decision support, emergency response, life-safety operations](https://www.elixirdata.co/industries/emergency-services/) [🏛 Public Sector Sovereign deployment, tenant isolation, data residency controls](https://www.elixirdata.co/industries/public-safety/) [⚙ Regulated Manufacturing Supply chain intelligence, operational safety, pre-deployment validation](https://www.elixirdata.co/industries/discrete-manufacturing/) Don't see your fit? **Every solution is built on the same Decision Harness.** [Request a custom briefing →](https://www.elixirdata.co/contact-us/) - Industries - [Industries Overview](https://www.elixirdata.co/industries/) - [Discrete Manufacturing](https://www.elixirdata.co/industries/discrete-manufacturing/) - [Industrial Automation](https://www.elixirdata.co/industries/industrial-automation/) - [Robotics & Physical AI](https://www.elixirdata.co/industries/robotics-and-physical-ai/) - [Energy & Utilities](https://www.elixirdata.co/industries/energy-utilities/) - [Transportation](https://www.elixirdata.co/industries/transportation/) - [Shipping & Logistics](https://www.elixirdata.co/industries/shipping-and-logistics/) - [Telecommunications](https://www.elixirdata.co/industries/telco/) - [Banking & Financial Services](https://www.elixirdata.co/industries/banking-and-financial-services/) - [Travel & Hospitality](https://www.elixirdata.co/industries/travel-and-hospitality/) - [Public Safety](https://www.elixirdata.co/industries/public-safety/) - [Emergency Services](https://www.elixirdata.co/industries/emergency-services/) Industries AI Decision Infrastructure for Modern Industry Operations. Governed, context-aware AI across industrial systems, critical infrastructure, regulated services, and public operations. Industrial Systems [⚙ Discrete Manufacturing Quality, traceability, and production governance](https://www.elixirdata.co/industries/discrete-manufacturing/) [⌘ Industrial Automation Safety boundaries for autonomous industrial systems](https://www.elixirdata.co/industries/industrial-automation/) [◉ Robotics & Physical AI Governed autonomy with human authority](https://www.elixirdata.co/industries/robotics-and-physical-ai/) [⚡ Energy & Utilities Safe, real-time grid decision governance](https://www.elixirdata.co/industries/energy-utilities/) Mobility, Networks & Travel [↗ Transportation Governed transport decisions with full lineage](https://www.elixirdata.co/industries/transportation/) [▦ Shipping & Logistics Routing, asset movement, and traceability](https://www.elixirdata.co/industries/shipping-and-logistics/) [⌁ Telecommunications Accountable AI for network operations](https://www.elixirdata.co/industries/telco/) [✦ Travel & Hospitality Governed, context-aware guest personalization](https://www.elixirdata.co/industries/travel-and-hospitality/) Regulated & Public Services [🏦 Banking & Financial Services Defensible decisions and regulatory controls](https://www.elixirdata.co/industries/banking-and-financial-services/) [🏛 Public Safety Explainable decisions with accountable lineage](https://www.elixirdata.co/industries/public-safety/) [⚕ Emergency Services Governed intelligence for critical response](https://www.elixirdata.co/industries/emergency-services/) **Industry-specific operations.** One governed Decision Harness. [Explore all industries →](https://www.elixirdata.co/industries/) - Enterprise - [Agent Registry](https://www.elixirdata.co/enterprise/agent-registry/) - [AgentOps](https://www.elixirdata.co/enterprise/agentops/) - [Agent Identity & Access](https://www.elixirdata.co/enterprise/agent-identity-and-access/) - [Evaluation and Optimization](https://www.elixirdata.co/enterprise/evaluation-optimization/) - [Trust Center](https://www.elixirdata.co/enterprise/trust-center/) - [Privacy, Security & Compliance](https://www.elixirdata.co/enterprise/privacy-security-compliance/) - [Data Residency & Isolation](https://www.elixirdata.co/enterprise/data-residency/) - [Admin & Access Control](https://www.elixirdata.co/enterprise/agent-identity-and-access/) - [SLAs & Support](https://www.elixirdata.co/enterprise/ai-sla-support/) Enterprise Enterprise control without slowing execution. 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[Request Trust Package →](https://www.elixirdata.co/enterprise/privacy-security-compliance/) - Resources - [Executive Blueprint](https://www.elixirdata.co/resources/executive-blueprint/) - [Blog](https://www.elixirdata.co/blog/) - [Customer Outcomes](https://www.elixirdata.co/resources/customer-outcomes/) - [Trust & Assurance](https://www.elixirdata.co/trust-and-assurance/authority-model/) Resources ### [Executive Blueprint Strategic guide for enterprise AI leaders](https://www.elixirdata.co/resources/executive-blueprint/) ### [Blog Insights on modern AI systems](https://www.elixirdata.co/blog/) ### [Customer Outcomes Proof of impact for clients](https://www.elixirdata.co/resources/customer-outcomes/) ### [Trust and Assurance Framework for governed decisions](https://www.elixirdata.co/trust-and-assurance/) - Company - [About Us](https://www.elixirdata.co/about-us/) - [Leadership](https://www.elixirdata.co/leadership/) - [Careers](https://www.elixirdata.co/careers/) - [Press & News](https://www.elixirdata.co/press-and-news/) - [Contact](https://www.elixirdata.co/contact-us/) - [Governance and Transparency](https://www.elixirdata.co/governance-and-transparency/) About ### [About Us Learn more about our mission and vision](https://www.elixirdata.co/about-us/) ### [Leadership Meet our experienced executive leadership team](https://www.elixirdata.co/leadership/) ### [Careers Join us in building enterprise AI solutions](https://www.elixirdata.co/careers/) ### [Press & News Stay informed with latest company updates](https://www.elixirdata.co/press-and-news/) ### [Contact Get in touch with our team directly](https://www.elixirdata.co/contact-us/) Company ### Governance and Transparency Discover the principles, leadership, and culture driving our approach to secure and governed enterprise AI. 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[View Plans →](https://www.elixirdata.co/pricing/) [Get Demo](https://www.elixirdata.co/context-os/demo/) [LLMS TXT](https://www.elixirdata.co/llms.txt) [LLMS Full TXT](https://www.elixirdata.co/llms-full.txt) [AI Context JSON](https://www.elixirdata.co/ai-context.json) [Decision Infrastructure](https://www.elixirdata.co/blog/tag/decision-infrastructure) # Media algorithm governance decision infrastructure [Navdeep Singh Gill](https://www.elixirdata.co/blog/author/navdeep-singh-gill) | 23 April 2026 Media algorithm governance decision infrastructure 13:57   ## How ElixirData Context OS Governs Content Moderation, Ad Placement, and Recommendation Decisions Across Media Platforms ### **Direct Answer** Media platforms need **decision infrastructure for [AI agents](https://www.akira.ai/digital-workers/)** because content moderation, ad placement, and recommendation decisions are not just technical outputs. They are governed decisions with legal, commercial, and societal consequences. **[ElixirData Context OS](https://www.elixirdata.co/)** provides that infrastructure through Context Graph, Decision Boundaries, Decision Traces, and a Governed Agent Runtime so every high-scale platform decision is context-aware, policy-bounded, explainable, and audit-ready. ## Key Takeaways - Media platforms are decision systems, not just content systems. - [**Decision infrastructure for AI agents**](https://www.elixirdata.co/blog/decision-infrastructure-cross-industry-criticality) makes platform behavior governable. - [Context Graph](https://www.elixirdata.co/blog/context-graphs) turns fragmented content, user, policy, and regulatory signals into decision-grade context. - Decision Boundaries enforce governance at runtime before unsafe actions execute. - Decision Traces make algorithmic decisions reviewable, defensible, and auditable. - [**ElixirData Context OS**](https://www.elixirdata.co/)helps platforms move from black-box algorithmics to accountable decision intelligence. [![CTA 2-Jan-05-2026-04-30-18-2527-AM](https://www.elixirdata.co/hs-fs/hubfs/CTA%202-Jan-05-2026-04-30-18-2527-AM.webp?width=878&height=133&name=CTA%202-Jan-05-2026-04-30-18-2527-AM.webp)](https://www.elixirdata.co/) Media platforms no longer merely host content. They continuously decide what stays up, what comes down, which ads appear beside which content, and which recommendations shape what users see next. At that scale, algorithmic output becomes governance. A moderation action can affect free expression. An ad placement can create brand, privacy, or suitability risk. A recommendation can shape trust, reach, and public discourse. These are not isolated product events. They are high-consequence platform decisions. As scrutiny grows under the EU Digital Services Act, the UK Online Safety Act, privacy regulation, advertiser brand-safety requirements, and broader demands for algorithmic accountability, the core issue is becoming clearer. The problem is not a lack of AI. The problem is a lack of governed decision infrastructure. That is where **ElixirData Context OS** gives media platforms the operational layer required to make algorithmic actions traceable, enforceable, and reviewable in real time. ## What is decision infrastructure for AI agents in media platforms? **[Decision infrastructure for AI agents](https://www.elixirdata.co/blog/decision-infrastructure-cross-industry-criticality)** is the operational architecture that ensures AI-driven decisions happen within policy, authority, and evidence constraints. In media and AdTech, that means the system does not simply score, rank, classify, or optimize. It must also answer: - What policy was applied? - What context was considered? - What authority governed the action? - What evidence supported the decision? - What trace exists for appeal, audit, or regulatory review? **[ElixirData Context OS](https://www.elixirdata.co/product/context-os/)** provides this through four core primitives: | Component | What it does | Why it matters in media | | --- | --- | --- | | Context Graph | Connects content, users, policies, regulatory constraints, and historical signals | Gives AI agents decision-grade context instead of isolated inputs | | Decision Boundaries | Enforces legal, safety, business, and policy constraints at runtime | Prevents unsafe or non-compliant actions before execution | | Decision Traces | Records what was evaluated, why, and what action was taken | Supports appeals, audits, transparency, and accountability | | Governed Agent Runtime | Executes AI decisions within bounded autonomy | Enables scale without surrendering control | In one sentence: **ElixirData Context OS is [decision infrastructure for AI agents](https://www.elixirdata.co/blog/decision-infrastructure-cross-industry-criticality) that makes high-consequence platform decisions traceable, governed, and audit-ready.** ## Why is algorithmic governance now a media platform requirement? Modern media systems are under pressure from regulators, advertisers, users, and internal risk teams to explain not just what an algorithm did, but why it did it. That pressure is not unique to media. Similar governance demands are emerging in **decision infrastructure for observability**  in **[Context OS for legal operations](https://www.elixirdata.co/blog/context-os-legal-contracts)** and in sectors where Decision Traces determine whether an action can be defended after the fact. The pattern is consistent: once AI influences high-consequence outcomes, governance has to move upstream into the decision layer itself. That is why **decision infrastructure implementation** is now a platform requirement, not an optional maturity project. Media companies need infrastructure that makes algorithmic behavior governable before execution, not merely explainable afterward. ## Why do content moderation systems need decision infrastructure? Content moderation is often framed as a classification problem. In reality, it is a governance problem. A platform must balance: - freedom of expression - user safety - regulatory obligations - community standards - advertiser risk Most moderation stacks combine machine classification with human review. But when a platform needs to explain why a post was removed, which rule applied, or what context changed the outcome, the logic is often fragmented across models, reviewer notes, policy files, and tooling. ### How ElixirData Context OS improves moderation governance With **ElixirData Context OS** moderation decisions are evaluated inside a governed decision layer. A moderation Context Graph connects: - content signals such as text, image, video, and metadata - user history and behavioral context - platform policy rules - legal constraints tied to jurisdiction or content category [AI agents](https://www.akira.ai/digital-workers/) then operate within Decision Boundaries that encode moderation standards and legal obligations. Each action generates a Decision Trace that captures: - the signals assessed - the policies evaluated - the contextual factors considered - the rationale for the final moderation decision That changes moderation from a black-box outcome into a governed and reviewable process. This is especially important as platforms adopt multimodal systems. The governance question is no longer only about classification accuracy. It is also about execution design across image, video, language, and agentic workflows. That is why topics like [**VLM vs AI agent vs agentic video intelligence**](https://www.elixirdata.co/blog/vlm-vs-ai-agent-vs-agentic-video-intelligence) matter for internal linking here. A visual model may detect content, but an [AI agent](https://www.akira.ai/digital-workers/) system still needs governed context, policy, and traceability before action is taken. A useful comparison is **factory camera alert fatigue** In those environments, detection alone does not solve the operational problem because teams still need a governed mechanism to decide which alerts matter, which actions are safe, and which events require escalation. Content moderation has the same structure at platform scale. ## Why do ad placement and brand safety decisions need governance? Ad placement decisions determine more than fill rate. They determine: - which messages reach which audiences - which environments a brand appears beside - whether monetization happens inside privacy and suitability constraints Traditional AdTech systems optimize around targeting, bidding, and performance. But they often provide weak traceability around: - why a placement was allowed - whether brand safety standards were applied - how privacy rules influenced the final outcome ### How ElixirData Context OS governs ad placement **ElixirData Context OS** enables governed ad placement by combining commercial logic with policy logic. A placement Context Graph can connect: - page or content context - audience and behavioral attributes - advertiser constraints - campaign targeting logic - privacy and consent conditions - brand safety requirements AI agents then evaluate each placement inside Decision Boundaries that enforce: - advertiser suitability rules - privacy regulations such as GDPR and CCPA - content adjacency controls - internal monetization policies Each placement produces a Decision Trace that explains: - why the ad was eligible - what context was checked - what exclusions or constraints applied - why the placement was approved or rejected That gives platforms a stronger monetization foundation because governance becomes an enabler of advertiser confidence, not a blocker to scale. ## [![CTA 3-Jan-05-2026-04-26-49-9688-AM](https://www.elixirdata.co/hs-fs/hubfs/CTA%203-Jan-05-2026-04-26-49-9688-AM.jpeg?width=878&height=133&name=CTA%203-Jan-05-2026-04-26-49-9688-AM.jpeg)](https://demo.elixirdata.co/) ## Why do recommendation systems need accountability infrastructure? Recommendation systems shape what users read, watch, and believe. That makes them one of the most consequential decision systems in digital media. Most recommendation engines optimize for engagement. But when asked why a certain article, creator, or video was surfaced, the reasoning is often buried inside model behavior rather than exposed as governed logic. This creates a growing accountability challenge: - regulators want transparency - users want explainability - platforms need stronger control over influence and risk ### How ElixirData Context OS governs recommendations **ElixirData Context OS** turns recommendation logic into governed decision logic. A recommendation Context Graph can unify: - user preferences and interaction history - content attributes and quality signals - trust and safety policies - diversity and fairness rules - market-specific compliance constraints AI agents evaluate recommendations within Decision Boundaries that enforce: - content quality standards - diversity objectives - fairness constraints - transparency obligations Every recommendation generates a Decision Trace that records: - the relevant user context - the content selection logic - the policy checks applied - the rationale for recommendation eligibility That gives platforms a path toward recommendation accountability rather than opaque optimization. It also helps align algorithmic relevance with regulatory defensibility and user trust. ## What makes Context OS different from a standard AI stack? A conventional AI stack focuses on prediction. **ElixirData Context OS**  focuses on governed execution. That distinction matters because high-scale media decisions are not safe to leave as unbounded outputs. They require infrastructure that can combine: - **State** — what is happening now - **Context** — what relationships and conditions matter - **Policy** — what rules and authority govern action - **Feedback** — what outcomes should improve future decisions That is why **ElixirData Context OS** is not just another model layer. It is [decision infrastructure for AI agent](https://www.elixirdata.co/blog/decision-infrastructure-cross-industry-criticality) systems designed for environments where decisions must be both scalable and accountable. This is also why media is becoming a clear [**Enterprise AI Agent Use Case**](https://www.elixirdata.co/blog/enterprise-ai-agent-use-case) . Once agents influence trust, monetization, exposure, and compliance, the execution environment itself has to become governed. ## Cross-domain insight The underlying architecture is broader than media. The same decision pattern appears in [**Precision Agriculture Decision Traceability Infrastructure**](https://www.elixirdata.co/blog/precision-agriculture-decision-traceability-infrastructure) , where environmental variability and operational consequences require traceable action. It appears in **hospitality decision infrastructure** where personalization and service actions need governance and accountability. It appears in **Context OS for legal operations**, where evidence, authority, and auditability are core to defensible outcomes. These examples matter because they show that media platforms are not an isolated case. They are one instance of a larger enterprise shift toward governed AI execution. ## Conclusion Media platforms do not suffer from a shortage of algorithms. They suffer from a shortage of governed decision infrastructure. When a platform influences what millions of people see, read, and believe, every moderation action, placement decision, and recommendation becomes a governance event. **[ElixirData Context OS](https://www.elixirdata.co/product/context-os/)** gives media platforms the infrastructure to make those decisions: - context-aware - policy-bounded - traceable - explainable - audit-ready That is how platforms move from black-box algorithmic influence to accountable decision intelligence. And that is how they build trust at algorithmic scale. ## [![CTA-Jan-05-2026-04-28-32-0648-AM](https://www.elixirdata.co/hs-fs/hubfs/CTA-Jan-05-2026-04-28-32-0648-AM.jpeg?width=865&height=131&name=CTA-Jan-05-2026-04-28-32-0648-AM.jpeg)](https://demo.elixirdata.co/) ## Frequently Asked Questions 1. ### What is decision infrastructure for AI agent systems? [Decision infrastructure for AI agent](https://www.elixirdata.co/blog/decision-infrastructure-cross-industry-criticality) systems is the governance architecture that ensures AI-driven decisions are made within policy, authority, and evidence constraints. In media platforms, it helps govern moderation, ad placement, and recommendation decisions with traceability and accountability. 2. ### Why do media platforms need decision infrastructure for AI agent systems? Media platforms make millions of high-consequence decisions every day. Without decision infrastructure for [AI agent](https://www.akira.ai/digital-workers/) systems, those decisions remain difficult to explain, audit, defend, or govern under regulatory and public scrutiny. 3. ### How does ElixirData Context OS help with content moderation? **[ElixirData Context OS](https://www.elixirdata.co/product/context-os/)** helps content moderation by connecting content signals, user context, policy logic, and legal requirements in a Context Graph, then enforcing moderation rules through Decision Boundaries and recording every action in a Decision Trace. 4. ### How does ElixirData Context OS improve ad placement governance? **ElixirData Context OS** improves ad placement governance by evaluating eligibility, safety, targeting, privacy, and monetization logic within governed runtime constraints. That makes every placement decision more explainable and compliant. 5. ### How does ElixirData Context OS support recommendation accountability? **ElixirData Context OS** supports recommendation accountability by turning recommendation logic into traceable platform decisions. It captures the context, policy logic, and rationale behind each recommendation so platforms can improve transparency and auditability. 6. ### What makes ElixirData Context OS relevant for algorithmic accountability? **ElixirData Context OS** is relevant for algorithmic accountability because it provides the infrastructure needed to govern AI decisions before execution, not merely explain them after the fact.   ## Share Article - [![ElixirData Facebook](https://www.xenonstack.com/hubfs/xenonstack-facebook-service.svg)](https://www.facebook.com/share.php?u=https://www.elixirdata.co/blog/media-algorithm-governance-decision-infrastructure) - [![ElixirData X](https://www.xenonstack.com/hubfs/xs-twitter-white-updated-icon.svg)](https://twitter.com/intent/tweet?text=I+found+this+interesting+blog+post&url=https://www.elixirdata.co/blog/media-algorithm-governance-decision-infrastructure) - [![ElixirData LinkedIn](https://www.xenonstack.com/hubfs/xenonstack-linkedin-service.svg)](http://www.linkedin.com/shareArticle?mini=true&url=https://www.elixirdata.co/blog/media-algorithm-governance-decision-infrastructure) - [![ElixirData Email](https://www.xenonstack.com/hubfs/xenonstack-email-service.svg)](mailto:?subject=Check%20out%20https://www.elixirdata.co/blog/media-algorithm-governance-decision-infrastructure%20&body=Check%20out%20https://www.elixirdata.co/blog/media-algorithm-governance-decision-infrastructure) ## Table of Contents ## Explore Related Topics [Agentic Operations](https://www.elixirdata.co/blog/tag/agentic-operations) [Context Application](https://www.elixirdata.co/blog/tag/context-application) [Context Graph](https://www.elixirdata.co/blog/tag/context-graph) [Context OS](https://www.elixirdata.co/blog/tag/context-os) [Decision Graph](https://www.elixirdata.co/blog/tag/decision-graph) [Knowledge Graph](https://www.elixirdata.co/blog/tag/knowledge-graph) [Ontology](https://www.elixirdata.co/blog/tag/ontology) ![navdeep-singh-gill](https://www.elixirdata.co/hubfs/Imported%20images/navdeep-gill-ceo-xenonstack.svg) ## Navdeep Singh Gill Global CEO and Founder of ElixirData Navdeep Singh Gill is serving as Chief Executive Officer and Product Architect at XenonStack. He holds expertise in building SaaS Platform for Decentralised Big Data management and Governance, AI Marketplace for Operationalising and Scaling. His incredible experience in AI Technologies and Big Data Engineering thrills him to write about different use cases and its approach to solutions. [Explore More by Navdeep Singh Gill ![cta-blue-arrow](https://www.elixirdata.co/hubfs/Imported%20images/cta-arrow-blue.svg)](https://www.elixirdata.co/blog/author/navdeep-singh-gill) ## Subscribe to our Latest Technology Insights and Resources Subscribe Now ![slider-cross-icon](https://www.xenonstack.com/hubfs/slider-cross-icon.svg) ## Get the latest articles in your inbox Business Email ID \* Please enter a valid Business Email ID Company Name \* Please enter a valid Company Name Yes, I would like to receive the ElixirData newsletter as well as marketing emails regarding ElixirData products, services, and events. I understand I can unsubscribe at any time. 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