
SCIKIQ is a trailblazing no-code data platform that helps organizations integrate, curate, govern, and activate enterprise data across cloud, multi-cloud, hybrid, and on-premises environments. SCIKIQ works with the technology you already run, SAP, Oracle, Salesforce, databases, data lakes, warehouses, SaaS applications, AWS, Azure, and GCP, without forcing a rip-and-replace.
At its heart is Contextual Intelligence. SCIKIQ understands the unique semantics of enterprise data, connecting technical metadata with business definitions, relationships, rules, quality, lineage, and governance. The result is trusted, contextualized data that people, analytics, applications, and AI can understand and use.
SCIKIQ unifies the data lifecycle in one no-code platform:
• Integrate — Connect structured and unstructured data across applications, databases, files, APIs, SAP, and real-time sources using 200+ connectors and no-code pipelines.
• Curate — Profile, clean, transform, standardize, enrich, model, and contextualize data through automated data preparation.
• Govern — Manage metadata, catalog, data quality, lineage, privacy, policies, access, and stewardship across the enterprise.
• Activate — Deliver trusted data to BI, analytics, enterprise applications, data products, machine learning, AI copilots, and intelligent agents.
Instead of stitching together disconnected tools, SCIKIQ brings data integration, ETL, transformation, data quality, governance, catalog, lineage, semantic models, knowledge graphs, data products, and intelligence together on one unified platform. SCIKIQ works on top of your existing data architecture, reducing engineering complexity, bridging skill gaps, and accelerating time to value.
Recognized by Forrester, NASSCOM, YourStory, Inc42, and DataIQ for innovation in enterprise data and intelligence.
SCIKIQ is The No-Code Data Platform That Works for Your Business.
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FinOpsly is an AI Cost Governance platform. It brings AI, cloud, data platform and SaaS spend into one attribution, policy and control layer, so enterprises can price a workload before building it, attribute every dollar to an owner, hold spend inside budget under policy, and prove what landed in run-rate.
Your AI invoice is not what your AI costs. One request draws on model tokens, retrieval, warehouse queries, GPU capacity and storage, and only the first shows up on the AI bill. FinOpsly resolves all of it, plus the seats in procurement and the compute in an untagged cloud account, to the same dimensions: owner, team, application, line of business, customer and tenant. An AI initiative's full cost becomes one figure, charged back through one hierarchy in one cycle.
Workforce AI is the tools employees use: seats and per-user token draw across GitHub Copilot, Cursor, ChatGPT Enterprise and Microsoft 365 Copilot. Application AI is the AI your product ships: tokens, compute and data joined into cost-to-serve across OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex AI, SageMaker and Databricks.
PLAN. Price a workload from its architecture before any resource exists, across model APIs, GPU capacity, data platform consumption and storage, with assumptions visible. Compare it across candidate models on your measured usage.
EXPLAIN. Attribute spend to owner, team, application, line of business and business unit across 9+ hierarchy levels. Unified tagging reconciles providers that tag inconsistently, and AI-driven bulk labeling closes large key estates. Unattributed spend is reported in dollars.
ACT. Budgets per project, team and API key, with daily burn-rate monitoring. Anomaly detection with root cause, routed to the owner. Waste detection using FinOpsly's own algorithms and ML models. Commitment planning across AWS, Azure and Google Cloud. Policy-driven parking of idle compute.
PROVE. Chargeback across AI, cloud, data and SaaS in one cycle. Realized savings tracked into run-rate against a no-action baseline. Cost per call, cost per active user, and cost-to-serve per customer and tenant.
proof: 100% attribution of AI spend; chargeback from 12.4 days to under one day across 9+ levels; 26% realized savings in AWS and 17%+ in Azure at a payments client.
Built for CIOs, CTOs and platform leaders accountable for technology spend, FinOps and finance teams running chargeback, and engineering teams who need cost signal before they decide
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