Sferal

Sferal is a conversational AI platform that lets operations-heavy companies build internal systems and AI agents without writing code. Instead of dragging and dropping components, teams describe the app or workflow they want in plain language, and Sferal automatically proposes a structure, generates the full-stack application—complete with a user interface, backend logic, and database—and deploys it on secure infrastructure. The platform is purpose-built for logistics, distribution, manufacturing, and service businesses that still run on spreadsheets, email, and messaging apps, and it includes built-in governance, analytics, and integrations to bridge the gap between human processes and AI-driven automation.

• Conversational no-code builder: Describe your app or workflow in natural language; the system asks clarifying questions, suggests data models, and instantly generates pages, forms, and business logic.
• AI agent studio and marketplace: Create agents from documents, spreadsheets, videos, or live systems, or start from marketplace templates. Assign each agent a defined role like quote responder, document processor, or HR screener.
• Multi-LLM orchestration: Routes tasks across multiple large language models, automatically picking the best one for each job to balance quality, speed, and cost.
• Integrated front-end, back-end, and database: Every app includes a UI, backend logic, secure APIs, and structured data storage by default, plus debugging tools and automated security checks.
• Enterprise security and deployment options: Dedicated virtual machines, role-based access control, login and session management, audit logs, and the choice of cloud or on-prem deployment suit stricter IT environments.
• Connectors and data ingestion: Integrates with CRMs, ERPs, HR and finance tools, and ingests PDFs, emails, and spreadsheets so agents work with live business data.
• Governance and observability: A central console shows all agents and workflows, their usage, spend, and ROI, giving leadership a single control tower over AI efforts.

1. Sign up and start your free trial: Create an account on the Sferal website to access the platform and begin building.
2. Describe your app or workflow: Use the conversational interface to explain what you need—for example, “a dispatch board that shows pending orders, assigns drivers, and sends SMS updates.”
3. Let the system propose a structure: Sferal will ask clarifying questions about the data, rules, and interfaces, then generate the app’s pages, forms, and database schema.
4. Review and customize: Inspect the generated UI and logic. Refine fields, workflows, or business rules by continuing the conversation or manually tweaking components.
5. Add AI agents from documents or templates: Upload spreadsheets, PDFs, or connect live systems to create agents with specific roles, like a quote responder or document processor.
6. Deploy and monitor: Once satisfied, set access roles, deploy to your chosen environment, and use the governance console to track usage, spend, and ROI.

Sferal does not publish a detailed pricing grid, so most teams need to contact sales or use the ROI calculator to get a tailored estimate. A 7-day free trial is available, allowing organizations to build internal apps and experiment with AI agents before committing to a subscription. Pricing typically scales based on the number of users, apps, agents, and compute resources. Disclaimer: Pricing information may not be up to date. For the most accurate and current details, refer to the official Sferal website.

• Web application: Full-featured browser-based interface for building, deploying, and monitoring apps and agents.
• Cloud-hosted (SaaS): Standard deployment with dedicated virtual machines, accessed securely through the web.
• On-premises deployment: Option for organizations that need to keep data and execution within their own infrastructure.
• API access: Every built app exposes secure APIs that can connect with external tools or be used programmatically.
• Mobile accessibility: Users can access generated apps through mobile-friendly web interfaces, though the builder itself is desktop-oriented.

• Start with one high-impact agent: Identify a pain point like manual quote replies or document processing, build an agent for it, and prove value before expanding to more complex workflows.
• Involve domain experts in the conversation: The person who knows the process best should describe it to Sferal, not a technical go-between, to get the most accurate apps.
• Articulate decisions and data needs clearly: Even without coding, be explicit about which fields matter, what decisions the system should make, and where data should come from.
• Use the governance console early: Set up role-based access and track agent usage from day one so leadership can see ROI and prevent shadow AI.
• Leverage connectors to pull live data: Connect CRMs, ERPs, and email instead of uploading one-time exports—agents stay accurate and remain part of daily operations.
• Iterate in small cycles: Treat the initial generation as a draft; refine by rewriting rules or adding new data sources through conversation.

• Operations managers in logistics and distribution: Teams that need to automate dispatch, routing, and quote workflows without a dedicated engineering team.
• Manufacturing and industrial firms: Companies that want inventory dashboards, production tracking, and maintenance coordination built on live plant data.
• HR and people ops professionals: Departments looking to deploy AI-driven screening, onboarding, and employee self-service without IT queues.
• Finance and admin departments: Groups handling invoice extraction, multi-step approvals, and profitability reporting across systems.
• Mid-sized and large organizations with governance needs: Companies that require dedicated environments, audit logs, role-based access, and on-prem deployment options.
• Internal tool builders who lack developers: Business teams in service businesses who need secure, functional apps and agents but can’t hire a product team.