Democratize and productionize Gen AI across your entire org with Portkey
Portkey is highly praised for its robust functionality and ease of use, consistently receiving ratings between 4.5 and 5 out of 5 from users. The most frequent complaints revolve around occasional glitches, which seem to affect a minority of users based on the overall high scores. While there is limited information on pricing sentiment, the overall reputation of Portkey remains positive, with strong endorsements visible through social media mentions and high satisfaction ratings.
Mentions (30d)
0
Avg Rating
4.6
19 reviews
Platforms
2
GitHub Stars
11,123
968 forks
Portkey is highly praised for its robust functionality and ease of use, consistently receiving ratings between 4.5 and 5 out of 5 from users. The most frequent complaints revolve around occasional glitches, which seem to affect a minority of users based on the overall high scores. While there is limited information on pricing sentiment, the overall reputation of Portkey remains positive, with strong endorsements visible through social media mentions and high satisfaction ratings.
Features
Use Cases
Industry
information technology & services
Employees
45
Funding Stage
Merger / Acquisition
Total Funding
$18.0M
368
GitHub followers
33
GitHub repos
11,123
GitHub stars
20
npm packages
Pricing found: $49/month, $49/month, $9, $49/month, $9/month
g2
What do you like best about Portkey?What I like best about Portkey is that it brings structure to what is otherwise a very chaotic part of building AI products. When you're working with multiple LLMs, APIs, and edge cases, things break silently—and debugging becomes painful. Portkey acts as a unified gateway that gives you visibility, control, and reliability out of the box. The biggest win for me is observability + control. Having centralized logs, request tracking, cost insights, and performance metrics in one place makes a huge difference. Instead of guessing what went wrong, I can actually see how prompts behave, where latency spikes happen, and how much each request costs. It also simplifies multi-model integration. Rather than managing different APIs and retry logic across providers, everything runs through a single layer with built-in fallbacks, routing, and caching. That alone removes a lot of engineering overhead and lets me focus more on building features instead of infra. Another big plus is cost optimization. Features like caching, usage tracking, and model routing help avoid unnecessary LLM calls and keep spend predictable, which is critical when scaling. Review collected by and hosted on G2.com.What do you dislike about Portkey?What I dislike is that the platform can feel a bit complex initially. There’s a learning curve, especially if you’re new to LLMOps, and some areas like advanced analytics and documentation could be more polished. Review collected by and hosted on G2.com.
What do you like best about Portkey?We started using Portkey when our AI usage began getting messy across multiple models and providers. What stood out immediately was how it brings everything into one place without adding complexity. The biggest win for us has been visibility. You can actually see what’s happening with every request — cost, latency, failures — which makes debugging and optimization way faster. The observability layer alone is worth it, especially when you’re running multiple use cases in production. Review collected by and hosted on G2.com.What do you dislike about Portkey?The product is evolving quickly, which is great, but it also means some advanced analytics and customization options are still catching up. The UI can improve in a few areas. Review collected by and hosted on G2.com.
What do you like best about Portkey?The standout feature is the dashboard and analytics, which make observability and monitoring straightforward. Implementation is simple thanks to the available APIs, and there is a wide selection of LLM models and providers. It integrates smoothly into daily monitoring and troubleshooting routines. Review collected by and hosted on G2.com.What do you dislike about Portkey?The documentation falls short and often requires users to figure things out on their own. Additionally, price tracking does not work universally across all models, and for air-gapped setups, pricing updates must be done manually, which can lead to delays in getting accurate information. Review collected by and hosted on G2.com.
What do you like best about Portkey?Portkey is a comprehensive platform for gen AI builders os its AI gateway is smooth integration with large language models and its guardrails have a proactive usage with its prompt management and resilience helps to track costs as per use case and save repeated llm calls which has minimum 3-5 usage per day and its implementation is super easy for any beguines and its customer support is too friendly and responses quickly and its integration is super easy and efficient. we usally have a AI integration in large scale and has the guardrails for a limited usage and this software helps me alot. Review collected by and hosted on G2.com.What do you dislike about Portkey?the software has a lot of bugs and its complexcity for newcomers are too high with missing advanced analytics and its GUI documentation must be more flexible. Review collected by and hosted on G2.com.
What do you like best about Portkey?It allows you to attach metadata (key-value pairs) to each request, enabling cost breakdowns per user. Review collected by and hosted on G2.com.What do you dislike about Portkey?Lack of control You can’t choose your destination last minute. Once it’s activated, it takes you where it’s been enchanted to. Review collected by and hosted on G2.com.
What do you like best about Portkey?Single gateway to many LLMs so less work integrating separate APIs. Guardrails + compliance features help avoid bad or undesired outputs. Good security, standards (SOC2, ISO27001 etc.). Helps reduce costs via caching, fallback, routing to cheaper providers where possible. Review collected by and hosted on G2.com.What do you dislike about Portkey?Complex feature set. Pricing are high for smaller teams. Documentation or value for some advanced parts is still growing so a little gaps are still there in execution. Dependency on external LLM providers Review collected by and hosted on G2.com.
What do you like best about Portkey?What I appreciate most about Portkey is its simplicity and performance. It brings clarity and structure to API management, making it easy to track, debug, and optimize requests without needing a complex setup. The real-time monitoring tools and intuitive dashboard help identify issues instantly, and I really like how lightweight and fast the whole platform feels compared to traditional observability tools. The integration process is smooth, and the documentation is clear, even for more technical setups. Their support team is very responsive — you get real answers from engineers who actually understand the product. Review collected by and hosted on G2.com.What do you dislike about Portkey?Portkey is evolving quickly, so there are still a few advanced analytics and visualization options missing compared to older, enterprise-level tools. Also, some custom alert configurations could be more flexible. But the team is clearly improving things rapidly, and updates come frequently with noticeable improvements. Review collected by and hosted on G2.com.
What do you like best about Portkey?- Onboarding implementation is straightforward and is aided by good documentation - Its helped us maintain a high degree of reliability for production systems by features including fallbacks - The dashboard is helpful for daily observability with custom metadata filters and cost aggregates being particularly helpful - Helpful support and excellent community - The pace of adding new features is great Review collected by and hosted on G2.com.What do you dislike about Portkey?The ability to export response data from the dashboard is a missing piece. We have received data exports by interfacing with the support team in the past but the manual process adds friction. Review collected by and hosted on G2.com.
What do you like best about Portkey?Very easy to use, an amazing amazing support team, and a perfect product for running an LLM. Review collected by and hosted on G2.com.What do you dislike about Portkey?Nothing - I like everything about the tool - a few bugs here and there that I've run into, but the support team helped with all of them, which I'm grateful for. Review collected by and hosted on G2.com.
What do you like best about Portkey?IT helps me keep the logs of my usage, very easy to integrate. Gives me an estimate of my costing. Review collected by and hosted on G2.com.What do you dislike about Portkey?None as of now. Its solving the problems i expected it to. Review collected by and hosted on G2.com.
Anthropic just banned "claude -p" from their Quota - BIG MISTAKE!
So Anthropic just announced that starting June 15, claude -p, Agent SDK usage, Claude Code GitHub Actions, and third-party Agent SDK apps will stop counting against the normal Pro/Max interactive Claude usage. Instead, they now go into a separate monthly Agent SDK credit bucket. For Max 5x, that is apparently $100/month. Which sounds fine until you realize any serious autonomous agent setup can burn through that very fast. So yeah, if you built anything around: tickets -> agents -> hooks -> executor -> claude -p -> background automation you are probably cooked. I was building exactly this kind of thing with AgentiBridge / AgentiCore / AgentiHooks. Basically a framework for orchestrating Claude Code agents at scale. The idea was simple: run Claude Code not as a human sitting in the terminal, but as a worker inside a larger production system. And now Anthropic basically said: “Nice automation stack bro, please move to the paid SDK/API bucket.” FML. But I don’t think the solution is to cry forever or keep playing cat-and-mouse with tmux hacks. The real solution is model routing. My plan is this: Keep Claude for interactive operator work. Use Claude where the reasoning actually matters: architecture decisions debugging hard shit reviewing plans high-context coding anything that needs taste and judgment But for background agents, automation loops, disposable workers, CI-style jobs, and dumb task execution? Fuck burning premium Claude credits on that. Put LiteLLM, Portkey, or another LLM gateway in front. Then route the worker swarm to cheaper models: Gemini DeepSeek Qwen OpenAI-compatible models local/self-hosted models where possible Claude Code already supports custom model options through environment variables. So in theory, you can have different profiles/scripts/aliases that swap model routing depending on what you are doing. One profile for interactive Claude. Another profile for automation. Another profile for cheap background agents. So instead of every autonomous goblin using the expensive brain, you send the cheap goblins to cheap models and keep Claude for the operator layer. This was always where agent orchestration was going anyway. One model for everything is stupid. The future is gateways, routing, workload separation, and not letting every background agent torch your best model quota because it decided to rewrite the same YAML file 11 times. Anthropic didn’t kill agent orchestration. They just made the architecture more obvious. submitted by /u/nestorcolt [link] [comments]
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Deep analysis of Portkey-AI/gateway — architecture, costs, security, dependencies & more
Yes, Portkey offers a free tier. Pricing found: $49/month, $49/month, $9, $49/month, $9/month
Portkey has an average rating of 4.6 out of 5 stars based on 19 reviews from G2, Capterra, and TrustRadius.
Key features include: Production Stack for Gen AI Builders, Introducing the AI Gateway Pattern, End-to-end LLM Orchestration, Secure access to MCP tools, Integrate in a minute, A reliable source of truth for LLM pricing, Take the driver's seat with AI Governance, Recognised by industry leaders.
Portkey is commonly used for: AI Gateway implementation, Observability for AI models, Governance of AI systems, Prompt management for LLMs, Integration with GitHub workflows, Caching test results to optimize costs.
Portkey integrates with: OpenAI, AWS Lambda, GitHub, Azure, Google Cloud, Slack, Jira, Trello, Zapier, Microsoft Teams.
Portkey has a public GitHub repository with 11,123 stars.