Zams

Zams (zams.com), rebranded from Obviously AI in early 2025, is an AI agent platform that combines no-code predictive analytics with agentic automation. The platform's core promise is to let business users transform raw spreadsheet and database data into predictive models and autonomous AI agents within minutes, using plain-English commands rather than code or complex workflow builders. Founded by Nirman Dave — who previously built Obviously AI and was recognised in Forbes 30 Under 30 — Zams retains the no-code predictive analytics foundation of its earlier product while extending it into a broader agentic platform for back-office automation, forecasting, and decision support.

Zams' proprietary Z1 Engine transforms any large language model into a context-aware AI agent capable of retaining memory and executing multi-step actions across connected applications and data sources. On the analytics side, the platform provides an extensive library of classical machine learning algorithms — including decision trees, support vector machines, gradient boosting, and neural networks — accessible without coding, enabling teams to build classification, regression, time-series forecasting, and optimisation models directly from their existing data. The platform carries SOC 2 Type II, GDPR, and HIPAA compliance, with role-based access control and audit logging for enterprise deployments.

How Zams Works

Teams connect Zams to their existing data sources — spreadsheets, databases, CRMs, and business applications. From there, users can issue plain-English commands to build predictive models (for example, forecasting churn or sales trends), automate recurring reporting, or deploy AI agents that take action across connected tools. The no-code predictive analytics workflow inherited from Obviously AI allows users to select a dataset, choose what they want to predict, and have Zams automatically select and train an appropriate algorithm — handling feature engineering and model evaluation behind the scenes. On the agentic side, Zams agents can monitor data, generate reports, and trigger downstream workflows, with configurable human-in-the-loop approval steps for sensitive actions.

Key Features

• No-code predictive analytics — build, deploy, and scale machine learning models for classification, regression, time-series forecasting, and optimisation without writing code
• Z1 Engine — proprietary technology that converts any large language model into a context-aware agent with persistent memory and multi-step action capabilities
• Extensive algorithm library — access to classical ML algorithms including decision trees, support vector machines, gradient boosting, and neural networks, with automatic model selection
• Agentic automation — deploy AI agents that automate back-office tasks such as reporting, follow-ups, research, and data entry through plain-English commands
• Model abstraction and tool chaining — agent-state management and tool chaining capabilities for building multi-step automated workflows across connected applications
• Built-in model testing and monitoring — comprehensive testing, analytics, and ongoing monitoring of deployed predictive models with built-in cost management
• Customer retention and churn prediction — predictive AI tools to identify at-risk customers and trigger personalised retention workflows
• Human oversight controls — configurable approval steps allowing humans to intervene, approve, or stop agent actions on sensitive workflows
• Enterprise compliance — SOC 2 Type II, GDPR, and HIPAA compliant with role-based access control, audit logs, and data residency options
• Rapid deployment — designed to take teams from raw data to operational predictive models or agents within roughly two weeks

Zams Pricing

• Starter — from $50/month (billed annually; $60/month billed monthly) — Includes core no-code predictive analytics, access to the algorithm library, and a limited allocation of agent tasks. Suited to individuals and small teams getting started with predictive modelling and automation.
• Growth — from $100/month (billed annually; $120/month billed monthly) — Expanded agent task limits, additional model deployments, and broader integration access for teams running predictive analytics and automation as part of regular workflows.

Higher-volume and enterprise tiers with custom integrations, dedicated support, and advanced compliance features are available via sales, with reported enterprise deployments starting around $1,000/month. Always verify current rates at zams.com/pricing.

Who Should Use Zams?

Zams is well suited to data analysts, operations teams, and decision-makers who want predictive AI capabilities — forecasting, churn prediction, optimisation — without needing a data science team to build and maintain models. Its agentic layer adds value for teams looking to automate recurring reporting and back-office tasks using natural language rather than configuring rule-based workflow tools. Because Zams' agentic features depend on integrations with existing business systems (CRM, email, communication tools), organisations without these systems already in place will get less immediate value. Teams that need heavy customisation of ML pipelines or deep statistical modelling may find a dedicated data science platform a better fit, while Zams excels at making predictive analytics accessible to non-technical business users.

Frequently Asked Questions