AI visibility report
Inngest ranks #2 in Workflow Orchestration & Durable Execution AI search.
Outside the top three on 16 of the 25 prompts buyers actually ask.
Temporal is cited on 11 of those losses.
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Also benchmarked
Inngest appears in another vertical
Track Inngest across these prompts daily.
Start free trial#2 among 11 vendors · still absent from 80.7% of tracked prompt responses
Top-3 citations across 150 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Grok
ChatGPT
Gemini Search
Google AI Mode
Bing Copilot
PerplexityVisible, but narrative can improve. Inngest ranks #2 on presence but #4 on sentiment. The brand appears relatively often, but competitors may be getting more favorable language when they appear.
Where Inngest is losing
Prompts where competitors are visible and Inngest is not.
These prompt-level losses are the first prompts to track and repair.
Where Inngest is winning5
Which workflow orchestration platforms let developers write workflows in plain code without learning a proprietary DSL or YAML configuration?
Avg # 1.0 · 1 platform
Looking for a workflow platform with strong LLM provider integrations for building AI agent pipelines with retry logic and state persistence — what should I look at?
Avg # 2.0 · 2 platforms
What orchestration tools are battle-tested for production use at high scale — which ones do high-growth startups rely on for mission-critical workflows?
Avg # 2.0 · 1 platform
I'm evaluating durable execution platforms for a startup with complex multi-step background jobs — which ones have the fastest time to value?
Avg # 2.3 · 4 platforms
What durable execution tools work well with serverless compute platforms so individual workflow steps run as isolated functions without dedicated workers?
Avg # 4.0 · 2 platforms
Where Inngest is losing5
Which durable workflow platforms support versioning workflows so you can deploy code changes without breaking in-flight executions?
Competitors on 4 platforms
Track this promptWhat durable execution tools guarantee at-least-once execution and idempotency so workflows never silently drop work in a distributed system?
Competitors on 4 platforms
Track this promptWhat workflow orchestration tools support human-in-the-loop workflows where execution pauses indefinitely until a person approves the next step?
Competitors on 4 platforms
Track this promptWhat durable workflow platforms support scheduling and cron-like triggers natively so teams can replace job schedulers without adding another tool?
Competitors on 3 platforms
Track this promptWhich workflow orchestration platforms integrate natively with event streaming platforms to trigger workflows from topic messages?
Competitors on 3 platforms
Track this prompt
Track Inngest daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Inngest is an event-driven durable execution platform founded in 2021 and headquartered in San Francisco. It enables developers to build reliable workflows, background jobs, AI agent pipelines, and scheduled tasks by wrapping ordinary functions in SDK-level steps—eliminating the need to manage queues, schedulers, state machines, or worker infrastructure. The platform handles automatic retries, state persistence, flow control, and observability, processing billions of workflows monthly. SDKs are available for TypeScript/JavaScript, Python, Go, and Kotlin/Java, with deployment support for Vercel, Netlify, Cloudflare, and any HTTP-capable cloud. Customers include SoundCloud, ElevenLabs, Cohere, TripAdvisor, Replit, and GitBook. Inngest is SOC 2 compliant with HIPAA BAA available for regulated workloads.
Inngest is a managed durable execution and workflow orchestration platform that lets developers make any code fault-tolerant by wrapping it in SDK steps. It replaces queues, schedulers, and state management with a single reliability layer accessed through TypeScript, Python, Go, or Kotlin SDKs. Core primitives include step.run (automatic retry and exactly-once execution per step), step.sleep (delays spanning minutes to months), step.waitForEvent (human-in-the-loop or event-driven pause), and flow-control features such as per-user concurrency keys, throttling, debouncing, and prioritization. The platform ships with a local dev server for instant trace-level debugging, bulk Replay for incident recovery, and AI/agent tooling via AgentKit and MCP integration.
Key Facts
- Founded
- 2021
- HQ
- San Francisco, CA, USA
- Founders
- Tony Holdstock-Brown, Dan Farrelly
- Employees
- 10-25
- Funding
- ~$9.1M confirmed; ~$31–34M per PitchBook
- ARR
- ~$2.5M (Sacra estimate, late 2024)
- Customers
- Hundreds (Sacra, Q3 2024)
- Status
- Private
Target users
Key Capabilities10
- Durable step functions with automatic per-step retry and state persistence across failures
- Event-driven triggers via SDK, REST API, webhooks, and cron schedules
- Fine-grained flow control: per-key concurrency, throttling, rate limiting, debouncing, batching, and dynamic prioritization
- Real-time observability: structured traces, logs, and metrics with no added instrumentation
- Bulk Replay and Bulk Cancellation for incident recovery across thousands of runs
- AI and agent orchestration via AgentKit and step.ai primitives with LLM-aware tracing
- Multi-language SDKs (TypeScript, Python, Go, Kotlin/Java) with cross-language function invocation
- One-command local dev server (inngest-cli dev) with full trace visibility
- Self-hosting support (single binary, SQLite or Postgres persistence) under SSPL/DOSP license
- Enterprise compliance: SOC 2, E2E encryption middleware, SSO/SAML, HIPAA BAA, RBAC, audit trails
Key Use Cases8
- AI agent and multi-step LLM pipeline orchestration with retries and observability
- Serverless background jobs and task queues without managing workers or queues
- Long-running durable workflows spanning days, weeks, or months
- Scheduled and cron job execution with built-in alerting on missed runs
- Multi-tenant SaaS workflow engines with per-user concurrency fairness
- Event-driven data ingestion and processing pipelines
- Human-in-the-loop flows that pause and wait for external events or approvals
- Incident recovery via bulk replay of failed workflow runs
Inngest customer outcomes
50x faster processing; monthly infrastructure cost reduced from $2,800 to <$100
Switched from Google Cloud Composer to Inngest for financial data pipelines; processing speed and cost improved dramatically, with data availability dropping from up to a day to near-instant (under 30 minutes).
Sync time reduced from minutes/hours to near-instant (seconds in typical cases)
Replaced Google Cloud Tasks with Inngest for bi-directional Git Sync; per-space concurrency queuing eliminated hour-long waits for paying customers and reduced sync times to near-immediate.
51% reduction in false positives in AI code reviews
Migrated from a single-agent to multi-agent AI code review architecture orchestrated by Inngest; parallel agent execution with idempotency and flow control dramatically improved review accuracy.
100% event deliverability (from ~6% event loss on Kafka)
Switched from Kafka to Inngest for event processing; previously losing approximately 6% of events in transit, the team achieved complete event deliverability after migration.
Deployed within 1 week; significant reduction in developer context switching
Adopted Inngest for dynamic video generation and transcoding workflows; engineers could define complex multi-step pipelines entirely in code, significantly reducing infrastructure overhead and context switching.
Recent Trend
How AI describes Inngest3
Inngest : An event-driven, serverless-native platform that allows you to define workflows in TypeScript.
Which durable workflow platforms support TypeScript-native workflows with strong type safety and IDE autocomplete?
For a backend team looking to move away from fragile cron jobs and manual retry logic, Temporal is the industry-leading, albeit steep-learning-curve option, while Inngest is often cited as the easier, more modern alternative to adopt.
Looking for a workflow orchestration platform with a visual workflow replay UI so on-call engineers can debug a failed run without reading raw logs — what are my options?
Inngest : An event-driven platform specialized in low-latency triggering of serverless workflows, often used to bypass traditional queueing delays.
Which workflow platforms have the lowest latency for triggering a new workflow execution in response to an inbound webhook event?
Most cited sources8
26Inngest vs Temporal: Durable execution that developers love - Inngest
inngest.com·Documentation
- 20
AI and backend workflows, orchestrated at any scale
inngest.com·Documentation
- 16
How Inngest functions are executed: Durable Execution - Inngest Documentation
inngest.com·Documentation
- 8
Durable Execution - Reliable Workflows | Inngest
inngest.com·Documentation
- 5
Durable Workflows - Inngest
inngest.com·Documentation
- 3
Local development - Inngest Documentation
inngest.com·Blog Post
Alternatives in Workflow Orchestration & Durable Execution6
Inngest positions itself as a developer-first, serverless-native durable execution platform that eliminates queue infrastructure by wrapping application functions in SDK-level steps.
- Its primary differentiator versus Temporal is zero-infrastructure setup—no separate worker processes—with native Vercel/Next.js support and a one-command local dev server.
- Versus AWS Step Functions it offers code-centric workflow authoring without YAML/JSON state machine definitions.
- Versus Trigger.dev (the closest peer) Inngest emphasizes richer flow-control primitives (per-key concurrency, throttle, debounce, priority) and a more mature managed-cloud experience.
- The platform targets the 'reliability layer' positioning: replacing queues, schedulers, and state machines with a single managed service that developers interact with purely through code.
Reviews
Praised
- Exceptional developer experience and SDK ergonomics
- One-command local dev server with real-time traces
- Automatic retries and state management without boilerplate
- Eliminates context-switching between infrastructure and business logic
- Fine-grained per-user/per-resource concurrency control
- Bulk Replay for fast incident recovery
- AI agent traceability and observability out of the box
- Quick integration with Vercel and Next.js
Criticized
- Short trace retention on lower plans (24h Hobby, 7 days Pro)
- Step timeout ceiling of 2 hours may constrain very long-running operations
- SSPL license for self-hosted server is not a permissive open-source license
- Multi-node self-hosting not yet fully supported
- Retries consume additional execution quota
- Datadog observability is a costly add-on
No verifiable aggregate scores on G2 or Capterra were found for Inngest in public search results, consistent with the company's early-stage, developer-community-focused go-to-market. Qualitative feedback from published customer case studies and the developer community is strongly positive, with recurring praise for developer experience, local debugging tools, and built-in observability. Inngest was cited among notable developer-tool launches on Product Hunt by community members. Criticism, where present, focuses on plan-tier constraints (trace retention, concurrency limits) and SSPL licensing of the self-hosted server.
Pricing
Hobby (free forever): 50K executions/month, 5 concurrent steps, 24-hour trace retention, 3 users, community support. Pro (from $75/month): 1M executions included then $50 per additional 1M, 100+ concurrent steps, 7-day trace retention, 15+ users, granular metrics; HIPAA BAA available as add-on; Datadog observability add-on $300/month. Enterprise (custom): custom execution volume, 500–50K concurrent steps, 90-day trace retention, SAML/RBAC/audit trails, exportable observability, dedicated Slack support, SLAs. Usage-based volume discounts tier automatically from $0.000050 per execution at 1–5M down to $0.000015 per execution at 50–100M. Events are also metered (first 5M/day free on Pro).
Limitations
- Step execution is capped at a 2-hour maximum timeout per step, constrained by the hosting provider.
- Trace and log retention is 24 hours on the Hobby tier and 7 days on Pro (90 days on Enterprise).
- The Inngest server source code is published under the Server Side Public License (SSPL) with delayed Apache 2.0 open source publication, meaning self-hosting for commercial use requires compliance with SSPL terms rather than a permissive license.
- Multi-node self-hosted deployments (horizontal scaling of server components) are planned but not fully supported in initial v1.x releases.
- Advanced observability (Datadog export) is an add-on costing $300/month on Pro.
- No mobile application is available.
- Retries count as additional executions against plan quotas, which can accelerate usage on high-failure workloads.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Perplexity | ChatGPT | Bing Copilot | Gemini Search | Google AI Mode | Grok |
|---|---|---|---|---|---|---|
Capability2/5 cited (40%) | ||||||
Which durable workflow platforms support versioning workflows so you can deploy code changes without breaking in-flight executions? | ||||||
Which platforms handle long-running workflows that can sleep for days or months and resume exactly where they left off after an external event? | ||||||
I need a workflow engine that supports saga patterns for distributed transactions with automatic compensation on failure — what are my options? | ||||||
What workflow orchestration tools support human-in-the-loop workflows where execution pauses indefinitely until a person approves the next step? | ||||||
Which durable execution platforms handle fan-out scenarios where a parent workflow spawns thousands of child tasks and waits for all results? | ||||||
Developer Experience4/5 cited (80%) | ||||||
Which workflow orchestration platforms let developers write workflows in plain code without learning a proprietary DSL or YAML configuration? | ||||||
What durable execution tools have the best local development experience so engineers can step through a long-running workflow without deploying to a staging environment? | ||||||
Looking for a workflow orchestration platform with a visual workflow replay UI so on-call engineers can debug a failed run without reading raw logs — what are my options? | ||||||
Which durable workflow platforms support TypeScript-native workflows with strong type safety and IDE autocomplete? | ||||||
What workflow orchestration tools do platform teams recommend for reducing the custom infrastructure a product team needs to build for reliable background jobs? | ||||||
Integrations & Ecosystem3/5 cited (60%) | ||||||
What durable execution tools work well with serverless compute platforms so individual workflow steps run as isolated functions without dedicated workers? | ||||||
What durable workflow platforms support scheduling and cron-like triggers natively so teams can replace job schedulers without adding another tool? | ||||||
Which workflow orchestration tools integrate with observability platforms so traces span across workflow steps and external API calls? | ||||||
Which workflow orchestration platforms integrate natively with event streaming platforms to trigger workflows from topic messages? | ||||||
Looking for a workflow platform with strong LLM provider integrations for building AI agent pipelines with retry logic and state persistence — what should I look at? | ||||||
Performance & Reliability5/5 cited (100%) | ||||||
Which workflow orchestration platforms can scale to millions of concurrent workflow executions without degrading scheduler throughput? | ||||||
What durable execution tools guarantee at-least-once execution and idempotency so workflows never silently drop work in a distributed system? | ||||||
Which workflow platforms have the lowest latency for triggering a new workflow execution in response to an inbound webhook event? | ||||||
Which durable workflow platforms handle partial outages gracefully by resuming in-progress executions automatically when the system recovers? | ||||||
What orchestration tools are battle-tested for production use at high scale — which ones do high-growth startups rely on for mission-critical workflows? | ||||||
Setup & First Run4/5 cited (80%) | ||||||
What workflow orchestration platforms offer a managed cloud service with minimal ops overhead for a 10-person backend team? | ||||||
What's the easiest durable workflow platform to adopt for a backend team tired of managing unreliable cron jobs and retry logic from scratch? | ||||||
Which durable workflow tools have self-hosted options that are straightforward to deploy on a single server for a team not ready for managed services? | ||||||
I'm evaluating durable execution platforms for a startup with complex multi-step background jobs — which ones have the fastest time to value? | ||||||
Which workflow orchestration tools can a Node.js team integrate into an existing codebase without rewriting their business logic? | ||||||
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | Temporal | 34.7% | 35.2% | 12.0% | 22.0% | 28.7% | #22.8 | +0.38 |
| 2 | Inngest | 19.3% | 14.0% | 6.7% | 6.0% | 19.3% | #30.2 | +0.44 |
| 3 | Restate | 13.3% | 8.3% | 4.0% | 4.0% | 13.3% | #25.9 | +0.47 |
| 4 | AWS Step Functions | 12.7% | 8.3% | 2.0% | 0.0% | 10.7% | #27.4 | +0.44 |
| 5 | Kestra | 12.0% | 6.8% | 4.0% | 4.0% | 12.0% | #27.7 | +0.41 |
| 6 | Trigger.dev | 9.3% | 7.5% | 0.7% | 0.7% | 9.3% | #35.4 | +0.30 |
| 7 | Orkes | 8.7% | 3.8% | 1.3% | 6.0% | 8.7% | #27.2 | +0.32 |
| 8 | Prefect | 8.7% | 6.0% | 1.3% | 4.7% | 8.7% | #36.6 | +0.42 |
| 9 | Camunda | 7.3% | 5.5% | 2.7% | 6.0% | 7.3% | #50.8 | +0.26 |
| 10 | Hatchet | 3.3% | 2.3% | 2.0% | 1.3% | 3.3% | #17.9 | +0.58 |
| 11 | Windmill | 3.3% | 2.3% | 0.7% | 2.0% | 3.3% | #25.8 | +0.27 |
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