the agent runtime.
run reliable agents in production without reinventing the platform.
you've built the agent. now you're building the platform. queues, retries, state persistence, auth management... that wasn't the plan. inference.sh handles the infrastructure so you can focus on what your agent does, not how to keep it running.
production reality
agents fail. networks drop. apis timeout.
when something goes wrong, you need to know exactly what happened.
- • every tool call is stored before it runs
- • execution is graph-backed. you see the full decision chain
- • chat history persists. close the browser, come back tomorrow
when the 3am incident happens, you can trace exactly what the agent did.
durable execution
event-driven, not long-running. if a tool fails, it doesn't crash your agent loop. state persists across invocations.
tool orchestration
150+ apps as tools via one API. structured execution with approvals when needed. full visibility into what ran.
observability
real-time streaming and logs for every action. see exactly what your agent is doing.
pay-per-execution
no idle costs while tools run or waiting for results. you're not paying to keep a process alive.
plug any model, swap providers without changing code
why we built this
we've heard it all before
real quotes from developers hitting the same walls.
"The agent framework is not the moat. Prompt engineering is not the moat. The base LLM is not the moat. The specialized tools that encode domain knowledge—are the moat."
"I spent 6 hours debugging a workflow that had zero error logs. When something breaks at 2 AM, I don't want to trace through 47 nodes. I want to see exactly what payload caused the issue."
"I felt like a 'button person' in my IDE. The agent works in quanta—cut off by time every 2 minutes. Long tasks require pipeline thinking, not chat sessions."
"Our multi-step agent produced great results but took 45+ seconds. Users thought it crashed. If they see the internal monologue, they wait. If they see a spinner, they leave."
"Spent 10 hours deploying agents on EC2... $13/mo per agent. Switched to serverless: 10 cents. Why is this so hard?"
"Systems record that a ticket was escalated, but not why it happened. Without that reasoning, agents treat every edge case as a brand new problem."
agent architecture
full agent primitives
the building blocks for production agent systems
deep-agents
agents spawn sub-agents as tools. orchestrator delegates to specialists. results flow back up the chain. the main context stays focused on the original task.
human in the loop
agent pauses, shows what it wants to do, waits for confirmation.
widgets
agents generate interactive UI on-the-fly. forms, selections, charts, visualizations — rendered inline.
widgets
agents generate beautiful UI with HTML and CSS to display data.
webhooks
call any API, receive async callbacks. your endpoints or third-party services.
client tools
execute on user's system — browser, local functions. sync request/response.
memory
built-in key-value store per conversation.
planning
built-in multi-step plans, resume after interruption. perfect for deep agents.
structured output
typed results back to orchestrator.
our philosophy
trust is not a feature.
it is a design constraint.
automation should never be a black box. systems should fail gracefully, not catastrophically.
read the trust manifesto →app library
tools your agents
can actually use
image generation, audio, video, code execution, and more. use directly or give to your agents.
not enough? create new apps fast. templates + coding agents make it insanely extensible.
create your own apps
start from templates. add code, packages, docs. deploy in minutes.
schemas become tool parameters automatically. your app shows up in the grid and can be used by agents and workflows.
create workflows
build a graph of apps. deploy as a single callable app.
drag and drop to build the graph. map io to connect steps. deploy as an app.
your way, your pace
start simple. go deep when you need to.
pip install inferenceshnpm i @inferencesh/sdkintegrations
real oauth.
durable, secure integrations with proper oauth flows. we handle token refresh, encrypted storage, and runtime injection.
- → encrypted storage (aes-256-gcm)
- → automatic token refresh
- → runtime injection — apps declare what they need
bring your own keys. use your own gcloud, azure, or aws billing & credits for ai models
explore BYOK integrations →
x402 ready
agentic payments
x402 enables instant, programmatic payments between agents and services. we handle the messy parts so your agents can pay without you shipping crypto UX.
- →managed wallets — agents can pay autonomously
- →controllable budgets — limits + policies per agent
- →no signups — paywalled endpoints on-demand
- →http-native — get 402, pay, retry
enterprise
self-host
deploy inference.sh in your vpc or on-prem for maximum control and privacy.
- keep data inside your network
- bring your own models + infra
- same workspace + api + runtime as cloud
- admin controls, auditability, and enterprise support
coming soon
deploy agents anywhere
your agent doesn't just use slack—it lives there. deploy to chat platforms and trigger on external events.
- →chat deployment — agents live in Slack, Discord, Telegram, WhatsApp
- →event triggers — fire agents on messages, file uploads, reactions
- →scheduled runs — cron-style execution for background tasks
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