Backplain - 2026 Pricing, Features, Reviews & Alternatives

Backplain is a governed multi-model AI workspace that consolidates access to 47 frontier models from nine providers, including OpenAI, Anthropic, Google, Meta, and Mistral, into a single interface. A patent-pending AI Firewall intercepts prompts before they reach any model, detecting and stripping PII, PHI, and custom-classified terms through three configurable enforcement modes: Hard Block, User Warning, and Silent Reconstitute. Every user session, prompt, model selection, and Firewall event is captured in a full audit log shared across desktop and mobile surfaces. Deployment options span multi-tenant SaaS (Personal, Team, Business tiers), customer-hosted cloud inside existing AWS, Azure, or GCP accounts, a dedicated Backplain Private Cloud, Sovereign Compute on bare-metal NVIDIA GPU servers colocated in a SOC 2 Type II certified Tier 3 data center in San Diego, and on-premises air-gapped installations for the strictest compliance requirements.

The platform targets regulated industries including legal, healthcare and clinical research, biotech, financial services, and defense and government contracting, with controls aligned to HIPAA, CMMC L2/L3, ITAR, CUI, and FedRAMP requirements. Core capabilities include simultaneous multi-model prompt execution with side-by-side comparison of up to 10 models per query, an admin and compliance console with SSO, SCIM, RBAC, model allowlists, policy enforcement, and a Sandbox Mode for auditor walkthroughs. Pre-built agents, including a Search Agent and a USPTO-connected Patent Agent, operate under the same Firewall policy as standard chat. A mobile iOS app extends multi-model chat, camera capture, and voice input across 47 models while preserving Firewall enforcement and audit log continuity on the same tenant as the desktop seat.

Flat-rate per-seat pricing carries no token costs, overage charges, or per-call billing, supporting predictable spend across tiers from individual users through large enterprise and sovereign deployments. Model Groups allow administrators to bundle models into named sets and assign different sets to different departments. Pro Services, delivered from the Carlsbad AI Lab, cover tiger-team sprints, model fine-tuning on proprietary data, fractional ML engineering, and fractional CISO advisory. Prompts, responses, and uploaded documents are not used to train any model.