Kheish is live · free · last verified 13 Sep 2026 · viability monitor
Kheish
Open-source daemon runtime that runs AI agents as durable services with crash recovery and approval gates.
Kheish is worth real attention if you have already felt an agent die because the caller disconnected, or you have hand-rolled suspend-and-resume for an approval step. The journaled checkpointing, detached runs, and async approval gates are the exact primitives most agent frameworks make you rebuild, and keeping model routing and credentials in the daemon is a clean separation. The honest trade-off is ecosystem: this is early, open-source, and self-hosted, so expect to wire your own tools and operate the daemon yourself. If you want plug-and-play integrations or a managed cloud, look at hosted agent platforms instead.
Verdict generatedVerified 9/13/2026 · liveness 43/100 · cite: rightaichoice.com/tools/kheish
- Platform engineers building durable agent infrastructure
- Incident response teams automating multi-tool triage with human oversight
- Developers deploying long-running tool-using agents in production
- Teams needing stateful agent sessions across multiple callers (CLI, HTTP, webhooks)
- End users or non-developers looking for a turnkey chatbot
- Teams wanting a batteries-included agent framework with pre-built integrations
- Simple single-turn Q&A use cases where daemon overhead outweighs benefit
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Skip Kheish if you want a hosted, managed agent platform with pre-built integrations and no daemon to operate yourself.
Self-hosting means you pay in engineer time and infrastructure: someone has to run, upgrade, and monitor the daemon on your own VM or cluster.
Kheish is free and open source under a community edition: $0/mo gets all core features including durable sessions, detached runs, approval gates, and checkpointing. That undercuts hosted agent platforms charging per-seat or per-run, but the real cost is operational—you supply the VM or cluster and the engineering time to run the daemon. It fits individual developers and platform teams already comfortable operating services; it fits poorly teams that would rather pay a vendor for a managed
In short
Kheish — Open-source daemon runtime that runs AI agents as durable services with crash recovery and approval gates. Best for Platform engineers building durable agent infrastructure, Incident response teams automating multi-tool triage with human oversight, Developers deploying long-running tool-using agents in production. Free to use.
What is Kheish?
Kheish — Open-source daemon runtime that runs AI agents as durable services with crash recovery and approval gates. Best for Platform engineers building durable agent infrastructure, Incident response teams automating multi-tool triage with human oversight, Developers deploying long-running tool-using agents in production. Free to use.
Kheish is an open-source, daemon-first agent runtime for platform engineers who need agents to survive the process boundary. Instead of bundling execution state into the client, Kheish keeps sessions, runs, approvals, tasks, assets, and routing inside a persistent daemon that stays alive independently of whatever caller started the work. That means one session can be reused across CLI, HTTP, webhooks, and automation, a run can pause for human approval and resume later, and an operator can inspect or control work started by another client. Core primitives include journaled checkpointing that recovers after SIGKILL, OOM kills, network drops, and daemon restarts; detached runs you can start now, stream later, suspend, and resume; async approval gates that halt before sensitive actions like a kubectl delete; and shared channels that give a single incident one durable thread for multiple agents and humans. Memory is separated into session history, recovered run memory, durable learnings, and promoted procedural skills so prompts stay scoped and bounded, with memory-context for inspection and memory-search for recall. Personas act as versioned identities carrying instructions, tools, and memory, so shipping an upgrade benefits every active session without breaking in-flight work. The daemon manages model routing, credentials, and output routing, so you can swap providers without redeploying callers. You drive it through an SDK, a CLI, or an HTTP/SSE control plane, and it runs as a single binary on a laptop, VM, or cluster with no hosted backend required. It is a runtime, not a framework and not a turnkey chatbot.
Key features
- Durable persistent sessions with journalled state and crash-safe checkpoints
- Journaled checkpointing that recovers after SIGKILL, OOM kills, network drops, and daemon restarts
- Detached runs — start work now, stream it later, inspect anytime, suspend and resume
- Async approval gates that halt before sensitive actions and continue from the same execution context
- Multi-agent shared channels (incident rooms) with humans and agents on one durable thread
- Daemon-managed routing of models, credentials, runtime settings, and outputs
- Runtime-swappable model providers (primary, fallback, standby slots) without redeploying callers
- Scoped memory split into session history, recovered run memory, durable learnings, and procedural skills
- memory-context command for view of prompt-eligible memory; memory-search for broader visible memory
- Persona-based versioned identities carrying instructions, tools, and memory, upgradeable across active sessions
- Callable code blocks (xHigh subagents) for workflow context
- Local docs and local code integration for tool use
- Captures for persisting raw observations into durable sessions
- HTTP and SSE control plane plus CLI for session and run management
- SDK for embedding Kheish into your own application
Our long-form take written Jul 22, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Models under the hood
as of 2026-09-23
Limitations
- Kheish is a daemon-first, open-source runtime that you self-host, so you own uptime, upgrades, log retention, and daemon operations; no managed cloud offering is described in the scraped material.
- It positions itself as a runtime rather than a framework, and the evidence centers on daemon, session, and approval primitives rather than on a curated tool library or opinionated agent patterns.
- Model routing is daemon-managed with swappable providers, but the live evidence names no specific underlying AI models.
as of 2026-09-13
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Is Kheish still active?
Kheish is live · free · last verified 13 Sep 2026 · viability monitor.
Viability score
How well maintained and how widely used is Kheish? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about Kheish?
How we verified this
Every listed fact about Kheish— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 13 Sep 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Kheish 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed limitations
- — changed description, use cases, our verdict, features, hidden costs, summary, pricing fit, who should skip it, pricing tiers, setup time, limitations, switching in, switching out
- — changed domain expiry
- — changed SSL certificate
- — changed pricing page
- — changed link health
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Kheish cost in 2026?
Kheish: Free to use. Pricing last verified 13 Sep 2026.
Plans compared
Every published Kheish tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Open Source (Community) | Free | — | Platform engineers and small teams comfortable self-hosting a daemon on their own laptop, VM, or cluster and wiring their own connectors.Adds: Starting tier and only published tier: $0/mo for all core features including durable sessions, detached runs, approval gates, and checkpointing, with community support via GitHub. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Kheish's pricing actually pencils out — and where peers do it cheaper.
Kheish is free and open source under a community edition: $0/mo gets all core features including durable sessions, detached runs, approval gates, and checkpointing. That undercuts hosted agent platforms charging per-seat or per-run, but the real cost is operational—you supply the VM or cluster and the engineering time to run the daemon. It fits individual developers and platform teams already comfortable operating services; it fits poorly teams that would rather pay a vendor for a managed
Has Kheish's pricing changed?
No plan price for Kheish has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Kheish?
Pick Kheish if you are Platform engineers building durable agent infrastructure, Incident response teams automating multi-tool triage with human oversight, Developers deploying long-running tool-using agents in production, Teams needing stateful agent sessions across multiple callers (CLI, HTTP, webhooks).
Look elsewhere if you are End users or non-developers looking for a turnkey chatbot, Teams wanting a batteries-included agent framework with pre-built integrations, Simple single-turn Q&A use cases where daemon overhead outweighs benefit, Serverless-only environments where a persistent daemon is not feasible.
Skip it if Skip Kheish if you want a hosted, managed agent platform with pre-built integrations and no daemon to operate yourself.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Kheish actually fits — and what changes day-one when you adopt it.
A monitoring webhook opens an incident, a planner agent drafts an investigation plan, two workers check latency dashboards and recent deployments, and the workflow halts at an approval gate before a rollback command runs.
Outcome: The daemon restarts mid-incident at step five, recovers journaled state, and the workflow resumes and completes without anyone re-running the investigation.
A review agent inspects a diff, posts findings to a shared channel, and pauses for a human reviewer to comment before continuing.
Outcome: The reviewer replies hours later and the run resumes from its checkpoint with the diff context intact, so no re-analysis is needed.
An agent collects data over several hours, periodically pausing to answer a user query, with durable learnings and procedural skills kept separate from the session transcript.
Outcome: Memory-context keeps prompts bounded while memory-search retrieves earlier findings, and the run continues across disconnects.
Use cases
- Run a multi-agent incident response workflow that survives a daemon restart mid-investigation and requires human approval before rollback.
- Build a persistent code review assistant that pauses for human feedback and resumes from checkpoint.
- Orchestrate a research agent that collects data over hours, pauses for user queries, and continues from scoped memory.
- Deploy a durable customer support escalation agent using versioned personas that maintain context across channels.
- Create a workflow where a planner agent delegates to worker agents and a reviewer agent verifies actions asynchronously.
- Operate a long-running data pipeline agent that calls external APIs, stores intermediates, and recovers from failure.
- Run an incident room where planner, workers, reviewer, and human share one durable session thread.
Setup time & first value
How long it actually takes to get something useful out of Kheish — broken out by persona, not the marketing-page minute.
For a developer already running services, expect under an hour to first value: start the local daemon from the single binary, run a session through the CLI, then add an approval gate. Platform teams deploying to a shared VM or cluster should budget a day for daemon deployment, SDK wiring, and connector setup, since connector specifics are not published and must be wired by hand.
Switching to or from Kheish
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From hand-rolled request-response agent code: move session and run state into the daemon and let the SDK drive sessions, runs, and streaming.
- →From an agent framework with client-side state: replace suspend-and-resume logic with detached runs and approval gates.
- →From queue-and-database glue: consolidate scattered state into daemon-owned sessions, assets, and routing.
- →From a hosted agent platform: self-host the single binary and repoint your callers at the CLI or HTTP/SSE control plane.
- ↗To a hosted agent platform: export session history and durable learnings, then rebuild orchestration on the vendor's managed runtime.
- ↗To an agent framework: extract persona instructions, tools, and skills, and re-implement durability in application code.
- ↗To a workflow engine: map shared channels and approval gates onto the engine's task and human-task primitives.
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Kheish”, and we withheld 6: 6 could not be judged, because “Kheish” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Kheish.
Official links
What are the best Kheish alternatives?
The closest alternatives to Kheish we list are xpander.ai, omnigent and Agno. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| xpander.ai | Freemium | Pricing not published | — |
| omnigent | Free | Free | — |
| Agno | Freemium | Pricing not published | — |
Alternatives to Kheish
View all
xpander.ai
Enterprise agent runtime that runs Claude Code, Codex, and OpenCode agents inside your own cloud with governance and budgets
Tools that pair well with Kheish
Common stack mates teams adopt alongside Kheish, with the specific reason each pairing earns its keep.
xpander.ai
Enterprise agent runtime that runs Claude Code, Codex, and OpenCode agents inside your own cloud with governance and budgets
omnigent
Open-source meta-harness that runs Claude Code, Codex, Pi and your own agents under one policy, sandbox and cost layer
Agno
Open-source Python SDK plus AgentOS runtime for serving agents as a REST API and MCP server you host yourself.
Kheish vs its closest rival
Kheish's closest head-to-head is with Spider Cloud — Choose Kheish if you need to run AI agents as durable, long-running services with crash recovery and human oversight. Choose Spider Cloud if you need fast, reliable web data extraction for LLMs or RAG pipelines. They solve different problems—one is a runtime for agentic workflows, the other is a data retrieval API. Verdict generated
Head-to-head comparisons
Kheish vs Spider Cloud
Choose Kheish if you need to run AI agents as durable, long-running services with crash recovery and human oversight. Choose Spider Cloud if you need fast, reliable web data extraction for LLMs or RAG pipelines. They solve different problems—one is a runtime for agentic workflows, the other is a data retrieval API.
GeneratedKheish vs Temporal Ai
Choose Temporal AI if you need a battle-tested, general-purpose durable execution platform with broad SDK support and cloud scalability, or if you're orchestrating complex microservices with Saga patterns. Choose Kheish if your primary focus is deploying long-running, tool-using AI agents with minimal overhead and you value built-in approval gates and detached run semantics. Both are open-source, but Temporal offers a cloud service while Kheish is entirely self-hosted.
GeneratedKheish vs Presto Voice
Presto Voice and Kheish serve entirely different needs. Presto Voice is purpose-built for QSR drive-thru automation with proven revenue lift, while Kheish is an infrastructure tool for developers building durable AI agents. Choose Presto Voice if you run a QSR chain and want to boost order value; choose Kheish if you engineer production agent systems that must survive crashes.
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