Running an AI agent safely and reliably inside your own product is a real engineering project: you need sandboxes so the agent can't do damage, orchestration so it uses the right tools in the right order, session and file handling, retry logic, and cost controls. HarnessRouter's pitch is to have already built all of that, so a product team can send a task through one API and get back finished work, instead of spending months building agent infrastructure from scratch. HarnessRouter lets developers run multiple sandboxed AI agents — including Codex, Claude Code, and Hermes, with more planned — behind a single API, producing real artifacts like code, files, videos, games, and documents for end users of the calling app. It handles the operational plumbing: sandbox environments, tool orchestration, file handling, sessions, streaming, retries, permissions, and cost controls, plus task tracing so developers can monitor what an agent did step by step. It's Y-Combinator backed and cites customers ranging from AI video-marketing startups to a top medical research institution using it to connect operational data into a unified 'academic brain.' Pricing is a 7-day free trial followed by tiered monthly plans (Developer, Production, Scale) with included credits and optional top-up balances that respect a set budget cap.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes entreprise et développeurs qui veulent déployer des agents IA de production fiables, avec gouvernance et sans dépendance à un seul fournisseur cloud | — | |
| 2 | Développeurs et équipes IA construisant chatbots, systèmes RAG, pipelines d'analyse de documents et traitement par lots, cherchant un coût d'infrastructure prévisible et une garantie de confidentialité | — | |
| 3 | Développeurs et organisations qui utilisent des LLM en production et veulent réduire la facture d'inférence sans changer leur code | — | |
| 4 | Développeurs et équipes qui construisent des agents IA ou des produits IA ayant besoin d'un accès de recherche structuré et unifié | — | |
| 5 | Créateurs solo, équipes internes, agences IA et responsables opérations voulant fiabiliser un agent IA avant/pendant la production | — | |
| 6 | Équipes en entreprise (finance, santé, retail, go-to-market) qui veulent une IA avec une mémoire partagée et auditable plutôt que des réponses individuelles incohérentes | — | |
| 7 | Entrepreneurs matériels, makers et porteurs de produit qui veulent une première estimation de faisabilité avant d'investir dans le développement | — | |
| 8 | Courtiers en fret et entreprises de logistique gérant un volume important de réservations de camions | — | |
| 9 | Entreprises multi-sites (retail, restauration rapide, immobilier, santé, assurance, vente B2B) voulant unifier appels, recrutement, formation et coaching | — | |
| 10 | Opérateurs et dispatchers de flottes de camions cherchant à optimiser l'attribution des trajets et l'utilisation des chauffeurs | — | |
| 11 | Associations et ONG avec des années de documents non structurés (rapports, comptes-rendus, politiques) | — | |
| 12 | Utilisateurs et équipes qui jonglent entre plusieurs outils IA (Claude, ChatGPT, Cursor...) et veulent un contexte partagé | — |
A toolkit for building AI "employees" that actually finish a job reliably — instead of a chatbot that just talks, Timbal helps a company wire up an AI agent that can look things up, take real actions in other systems, and behave consistently every time.
AI models on a phone-plan-style flat rate instead of a taxi meter — pay one predictable monthly price for a set number of requests across 40+ AI models, rather than watching a per-token bill climb with every word generated.
A price-comparison shopper for AI model calls — instead of always paying whatever your one chosen AI provider charges, Auriko checks prices across a dozen providers in real time and sends each request to whichever one is cheapest right now without changin
A search engine built for AI agents instead of humans — it hands back clean, structured answers instead of a page of blue links the agent then has to re-read and guess at.
A quality-control inspector for AI agents — before your AI assistant goes live and starts talking to real customers, AgentX tests it, points out exactly where it messes up, and suggests a fix, instead of you finding out from an angry customer.
A shared AI brain for your whole team — instead of everyone copy-pasting into their own private ChatGPT, PromptQL keeps one team-wide memory that gets smarter every time someone corrects it.
Describe a hardware idea in one sentence and get back, in about two minutes, whether it's realistically buildable, what it would cost to manufacture, and a rough 3D concept — before you spend real money finding out the hard way.
A voice AI that calls dozens of truck drivers at once to negotiate a load's price, so a freight broker gets a booked truck in minutes instead of working the phone all day.
An AI 'employee' for frontline businesses like retail and fast-casual chains — it answers phones, screens job candidates, coaches staff, and flags when someone's about to quit, all from the same conversation data.
An AI dispatcher for trucking companies — it looks at every driver, load and rule at once and works out the best assignment plan, instead of a human juggling spreadsheets and gut instinct.
A nonprofit's grant reports, board minutes and policy documents pile up over the years and become impossible to search by keyword — DocuSmart lets staff just ask a question in plain English and get an answer pulled from that pile.
Creed is a single Markdown file that describes who you are and how you work, which you plug into every AI tool you use — so you stop re-explaining your job, your team and your preferences to a new chatbot every time.
