Nola
Nola is a TypeScript superset that makes LLM inference a first-class language feature—introducing infer and ask constructs that compile to plain TypeScript so developers can write typed, observable LLM-backed functions with minimal glue.
Nola is coding software teams evaluate for coding. Use this page to review pricing, integration signals, and the best alternatives before you commit.
Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.
Review official source →Used in These Packs
Quick Overview
Best for: Coding
What it does
Coding software for decision-makers comparing workflow fit and alternatives.
Best fit
Coding
Pricing snapshot
Pricing available on request
Next step
Compare Nola with similar tools before you shortlist it.
Compare this tool before you shortlist it
Review alternatives, pricing posture, and workflow fit side by side.
Nola
Nola is a small toolchain and a TypeScript superset that makes LLM inference part of the language surface. It introduces infer functions and an ask expression so developers can declare LLM-backed functions whose inputs and outputs are TypeScript types; the toolchain lowers .tsi files to ordinary TypeScript and derives JSON Schemas for types at compile time. Nola includes a CLI, a local Nola Console for observability, editor tooling (VS Code extension and language server), and a developer workflow that runs offline from a committed replay ledger until you opt into a live provider.
Nola is a TypeScript superset (.tsi) where LLM inference is a language feature: ask for typed values or let the model call your code. Lowers to plain TS.
Own this listing?
Claim this page for a one-time $29 to add pricing, features, screenshots, verified owner details, and a clearly labeled 30-day category position after the profile is live.
Claim this listing for $29Key Features
Language-level inference (infer / ask)
Introduces infer functions and ask expressions as part of TypeScript where dot-prefixed parameters (e.g., .bio) form model-visible context and ask ..`prompt`<T> returns typed values validated against derived schemas.
Compile-time lowering and schema derivation
Nola lowers .tsi files to plain TypeScript before tsc/bundlers run, deriving JSON Schemas for each <T> from your TypeScript types at compile time.
Nola Console (observability)
Local trace viewer that records every ask and its events in a per-machine SQLite file; traces grouped by project, call, ask, and provider attempts with prompt, schema, provider, outcome and timing.
Editor & debugger integrations
Language server, tsserver plugin and VS Code extension (available); Zed and JetBrains integrations in progress; supports highlighting, diagnostics, hover, completion, go-to-definition and F5 debugging mapped to .tsi source.
CLI and tooling
Commands such as npm create nola@latest, npx nola-lang console, nola run, and skill install to scaffold projects, run the console, and add agent skills.
Observability hooks and receipts
Runtime emits events for ask lifecycle (onAskStart ... onInvocationEnd) and stores receipts; hooks observe events but cannot break an ask if they throw.
Offline-first starter and replay ledger
Starter project runs offline from a committed replay ledger so you can develop and test without an API key until you switch to a live provider.
Pricing
Starter scaffold and local runner work offline without an API key; project is Apache-2.0 licensed (open source). Live providers require your own API key or using the Nola Platform.
Use Cases
Structured extraction from text
Write infer functions that extract typed objects (e.g., Person) from free-form input using ask ..`prompt`<Type> and get a typed result validated at runtime.
Message triage and automated ticket creation
Chain asks and call native TypeScript functions (e.g., createTicket) from an infer function to triage customer messages and create backend tickets, returning typed results with ticket IDs.
Developers building LLM-backed business logic
Embed inference directly into TypeScript codebases where types are the contract, reducing schema/prompt/type drift and integrating with existing toolchains and databases.
Prompt tuning and observability
Use the Nola Console to inspect prompts, attempts, validation misses and durations to tune prompts and monitor model behavior in development.
Integrations
OpenAI and other model providers
Providers can be wrapped (example: nola({ baseUrl }, openai(...))) to resolve asks; live providers require API keys (starter runs offline until you switch).
Editors (VS Code, Zed, JetBrains)
VS Code extension and language server available today; Zed and JetBrains support in progress via the same Nola LSP.
Agents & skills
agent skill installer (npx nola-lang skill install) writes skill files for agents such as Claude, Code, Cursor, and Copilot so agents read project rules.
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Step 1: Create a project scaffold: run npm create nola@latest (requires Node ≥ 22).
- 2 Step 2: Write a .tsi file with infer functions and ask ..`prompt`<T> usages and import the generated .tsi from plain TypeScript.
- 3 Step 3: Run the project with nola run src/main.ts or npm start, and open the project in VS Code for editor and debugging support.
Support
Contact via [email protected] (listed on the site footer).
docs
Documentation and examples are available from the site (Documentation link in the product nav).
community
Community links such as Discord and GitHub are provided on the site for discussion and contributions.
issues
Report bugs or file issues on the project's GitHub Issues (GitHub link in the site nav).
API
Compare Nola with similar tools
See how it stacks up against alternatives
Related Tools
View all 54 →
FixBugs
FixBugs is an AI debugging agent for SREs and on-call engineers that auto-triages alerts, performs AI-powered root cause analysis, reproduces issues, and generates validated code fixes with reproduction tests. Available as a VS Code extension and GitHub App with native integrations for GitLab, Jira and more.
please do not escape
A curated dataset of sandbox environments for AI coding agents, published with a raw YAML data file and hosted on GitHub; intended as a discoverable, contributor-driven collection of examples and primary-source references.
Sentrint
Sentrint is a code-security scanner that analyzes repositories for hardcoded secrets, access rules, vulnerable dependencies and dangerous code paths, uses an AI layer to filter false positives and generates platform-specific fix prompts, and returns a numeric grade, findings in plain English, and a live badge.
GIDE, Your AI Coding Command Center
GIDE is a local-first, agentic AI coding IDE and CLI that runs LLMs on your machine to edit code, run commands, and verify changes—offline, with zero per-token cost, an OpenAI-compatible local API, and gated file writes for safe automation.
CodeTrain
CodeTrain is a local‑first, hands-on AI coding tutor that teaches developers by guiding them to write code in their own codebase step by step. It runs an agent on your machine, offers sandbox or repo modes, and provides team features (dashboards, onboarding journeys, SSO/SCIM, self‑host) for companies.
Convert Anything to Markdown
anyto.md converts URLs, PDFs, Office files, HTML, and images into plain, AI-friendly Markdown via a low-latency API so you can reduce token usage and reuse clean text in chats, agents, and RAG pipelines.
Premium Alternatives
templateai
TemplateAI is a paid Next.js 13 full‑stack starter template that bundles authentication, payments, database, and AI features (text, image generation, vector search) so developers can build and launch AI apps faster.
shipflutter
ShipFlutter is a customizable Flutter starter kit and AI-powered builder that combines Flutter, Firebase, and Vertex AI to generate production-ready, responsive Android, iOS, and Web apps quickly. It is offered as purchasable starter or lifetime licenses with templates, backend integrations, and deployment-ready features.
augment-code
Augment Code's Cosmos is an enterprise unified agents platform that runs software development agents at organizational scale, providing a Context Engine, agent runtime, reusable Experts, and security controls to accelerate code review, testing, incident response, and other SDLC workflows.