Plansera AI vs Switchyard: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Plansera AI and Switchyard — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Plansera AI
Plansera
AI paralegal that interviews E-2 visa clients, reads their evidence, checks eligibility, and produces a submission-ready business plan for a flat $100.
Key features
- Conversational Document Intake: An AI paralegal interviews the client in plain language and reads uploaded bank statements, leases and invoices, extracting figures and source/use of funds automatically.
- Built-in E-2 Eligibility Checks: Verifies substantial investment, capital at risk, traceable source of funds, non-marginal enterprise and a directing role before generating the plan.
- Deterministic Financials: Produces five-year revenue projections, cash flow and break-even analysis as clean tables and charts.
- Confirmed Use of Funds: Presents a categorized investment breakdown the client reviews and approves before generation.
- Submission-Ready Output: Generates a professionally designed PDF and an editable Word document formatted for the consulate.
- Flat-Fee Pricing: One price per plan with no subscription required.
Best for
- Immigration Attorneys: Drafting consulate-ready E-2 business plans for clients without outsourcing to a plan-writing firm.
- E-2 Visa Applicants: Producing an adjudication-standard plan grounded in their own financial evidence.
- Source-of-Funds Documentation: Automatically tracing and categorizing where investment capital originated.
- Financial Projection Building: Generating defensible five-year projections, cash-flow and break-even figures for a new enterprise.
- Document Review Prep: Assembling leases, invoices and bank statements into a structured case file.
Switchyard
NVIDIA
An open-source Rust proxy and library that routes LLM traffic across models and providers while preserving native OpenAI and Anthropic API compatibility.
Key features
- Protocol Translation: Converts between OpenAI Chat Completions, OpenAI Responses and Anthropic Messages formats so clients keep their native API while any backend serves the request.
- Multi-Backend Routing: Spreads traffic across vLLM, NVIDIA NIM, Ollama and any OpenAI-compatible endpoint, letting you point an existing coding agent at an open-source model without changing the agent.
- LLM Classifier Router: Uses request content to decide whether a given turn needs the weak or the strong model tier, cutting spend on turns that do not need frontier capability.
- Stage Router: Routes most turns from signals already in the conversation — tool results, errors, conversation stage — so no extra model call is needed to make the decision.
- Escalation Router: Runs every turn on the weak tier first, then has a judge read that answer and decide whether the same request should be re-sent to the strong tier.
- Random Routing for A/B Tests: Applies a fixed traffic split across targets for benchmarking, baselines and cost experiments.
- Operational Metrics: Exposes Prometheus metrics for requests, errors, latency, token counts and the overhead added by routing itself.
- Server or Library Deployment: Run it as a standalone Rust proxy configured by routes.toml, or embed switchyard-libsy in your own application so it decides the target and hands the model call back to you.
Best for
- Pointing Coding Agents at Open Models: Serve Claude Code or Codex from vLLM, NIM or Ollama without the agent knowing the API changed.
- Cost/Performance Optimization: Send routine turns to a cheap weak-tier model and reserve the strong tier for turns a classifier or judge says need it.
- Model A/B Benchmarking: Split traffic on a fixed ratio across two models to compare quality, latency and cost on real production requests.
- Provider Migration and Failover: Keep application code on one API shape while swapping or mixing the providers behind it.
- Embedding Routing in an Agent Runtime: Drop the routing algorithms into an existing gateway or agent framework via the library path without adopting a new HTTP stack.
- Operational Visibility: Track per-route latency, error rates and token spend through Prometheus to find which routes are actually costing money.