InsForge vs sizeless: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of InsForge and sizeless — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
InsForge
InsForge
Backend platform built for AI-assisted development, providing auth, database, storage, functions, and agent-focused AI integrations.
Key features
- Authentication & Authorization: Managed user auth system to add sign-up, login, and role-based access controls quickly, enabling secure agent and user interactions without custom auth development.
- Managed Database: Hosted relational database capabilities (Supabase-like) designed for agent-driven schemas and operations, allowing agents to read, write, and migrate data programmatically.
- Object Storage: Built-in storage for files and assets with APIs for upload, download, and access control, simplifying how agents handle media and persistent artifacts.
- Serverless Functions: Deployable functions to run custom business logic and glue code, enabling agents to invoke or extend backend behavior with server-side code.
- AI Agent Integrations: Native connectors and integration points to link any AI agent to backend services, allowing agents to orchestrate data, storage, and functions autonomously.
- Agent-Native Tooling: Developer SDKs and APIs optimized for agent workflows, enabling rapid connection of agents to backend resources and simplifying agent-driven app development.
- Rapid Provisioning: Ability to add authentication, database, storage, functions, and AI integrations to apps in seconds, accelerating prototyping and deployments for agent-enabled products.
- Authentication system for user and agent identity management
- Managed database functionality similar to Supabase features
- File/storage management for persistent assets
- Serverless functions for custom backend logic and extensions
- AI integrations and connectors to attach any agent
- Agent-native tooling to enable autonomous agent-driven app creation
- Quick onboarding and signup for rapid prototyping
- Open-source repository and community-driven development
Best for
- Agent-Driven App Development: Enable an AI agent to scaffold, store, and manage a full-stack application by provisioning auth, database, and storage automatically.
- Autonomous Agent Operations: Allow agents to run serverless functions and manage persistent data to complete multi-step tasks or background processes without human intervention.
- Rapid Prototyping: Quickly attach backend services (auth, DB, storage, functions) to proofs-of-concept where AI capabilities are central, reducing boilerplate work.
- Agent-Oriented Product Backends: Build products whose core workflows are driven by AI agents (chat assistants, automation bots) using agent-native integrations and APIs.
- Replacing Supabase for Agent Workloads: Migrate Supabase-style projects to an agent-first backend to enable autonomous agents to perform maintenance, migrations, and feature creation.
- AI-Augmented Team Tools: Provide teams with an agent-connected backend to let internal automation agents manage datasets, handle user onboarding, or process uploads.
- Providing a backend for applications built or managed by AI agents
- Rapid prototyping of full-stack apps with agent-assisted development
- Autonomous agent orchestration and app lifecycle management
- Embedding agent connectors and AI integrations into existing apps
- Replacing or augmenting Supabase-like backends with agent-focused features
sizeless
sizeless
Turns a smartphone video of an open trench into a centimetre-accurate 3D point cloud, CAD as-built plan and GIS-ready digital twin of buried utilities.
Key features
- Smartphone capture: Field crews record an open trench with a standard iPhone Pro — no specialist scanning hardware and no separate surveying appointment
- Centimetre-accurate point clouds: Reconstruction algorithms developed at ETH Zurich build a high-resolution 3D point cloud of the excavation from the video alone
- Standards-compliant CAD output: Generates as-built plans in DWG and DXF, with couplings and pipe runs identified and measurements simplified
- 3D digital twin and GIS export: Produces a model of the pipe route including building entries that drops into existing GIS systems
- Works without GPS: Captures basement sections and building entry points where GNSS-based surveying fails
- Immediate backfilling: Because capture takes minutes, trenches close right after filming instead of waiting on a survey crew
- Documentation in about 72 hours: Complete records arrive weeks earlier than conventional surveying, enabling prompt connection billing
- Third-party utility capture: Records crossing utilities and as-laid geometry as unbroken 3D evidence, replacing hand sketches
Best for
- A utility network operator documenting residential service connections without booking a surveyor for every site
- A contractor closing a trench the same day instead of leaving it open pending a survey appointment
- Capturing a building entry point in a basement where GPS-based surveying cannot get a fix
- A district heating project producing as-built DWG plans for regulatory sign-off
- Spotting a laying error in the 3D point cloud before backfilling, while the fix is still cheap
- Feeding as-built pipe geometry into a GIS system for long-term network maintenance planning