Foglamp Review (2026): Pricing, Features & Honest Verdict

Foglamp Review: The Quick Verdict

Foglamp is an observability platform for AI agents that tracks the cost, latency, and quality of every LLM call. Two lines of code instrument your agents, and you get traces, evals, and alerts. Best for teams shipping AI agents to production. Price: free tier with 10,000 spans/mo, Pro at $49/mo. Rating: 7.5/10.

We found Foglamp on Product Hunt under the line ship AI agents you can actually see, and it scratches a real itch. Anyone who has put an LLM agent in front of users knows the dread of not knowing what it costs, how slow it is, or whether the output quietly went bad. Foglamp is built to remove that blindness.

What is Foglamp?

Foglamp is monitoring and observability for AI agents and LLM applications. Once instrumented, it captures the cost, latency, errors, and quality scores of every model call your app makes, then presents them so you can actually reason about them. Instead of staring at a vague OpenAI or Anthropic bill at the end of the month, you see exactly what each call cost, broken down by model, by agent, and even by customer. The selling point is how little it takes to set up: two lines of code instrument every generateText or streamText call.

It is built by Foglamp Labs, with co-founder Gustavo Fior visible in the company’s own testimonials. The tool is aimed at engineering teams shipping agents to production, and it is notably tuned for builders using the Claude Agent SDK, though the tracing model is general. The framing is honest about the problem: cost, latency, errors, and eval scores are all there in your agent, but invisible until something tracks them. Foglamp’s whole job is to make them visible before a bad deploy or a runaway cost regression reaches your users.

What Are Foglamp’s Key Features?

Cost intelligence

Foglamp tracks exactly what every call costs and slices it by model, agent, and customer. This is the feature most teams will feel immediately, because LLM bills are notoriously opaque and a single bad prompt change can multiply spend overnight. Knowing which agent or which customer is burning the budget turns a scary monthly invoice into something you can manage line by line.

Distributed traces

Every agent run shows up as a waterfall trace, with the exact prompt and response captured per span. When an agent misbehaves, you can open the run and see precisely what it was fed and what it produced at each step. For debugging multi-step agents, where the failure is usually three calls upstream of where it surfaces, this is the difference between a five-minute fix and an afternoon of guesswork.

Evals on production traffic

Foglamp scores real production traffic using code-based checks and LLM-as-judge evaluations. Rather than only testing in a sandbox before launch, you keep grading the live output and catch quality drift as it happens. This is the feature that catches the slow, silent degradation that unit tests never will.

Alerts

You set threshold rules on cost, latency, and error rate, and Foglamp tells you when something crosses the line. On the Pro tier it pushes those alerts to email and Slack. The testimonial on its own site says it all: a 10x cost regression caught three days after shipping. That is the kind of thing that, uncaught, becomes a horror story in your billing dashboard.

How Much Does Foglamp Cost?

Foglamp’s free tier is real and usable: 10,000 spans per month, 3 days of data retention, one project, one alert, and five evals, with unlimited agents, workflows, traces, and team members. That is enough to instrument a small app and feel the value before paying. The Pro tier is $49 per month and lifts the limits hard: 1,000,000 spans per month, 14 days of retention, five projects, ten alerts, and twenty evals, plus the Foggy AI assistant, email and Slack alerting, and priority support. Enterprise is custom, with 90-plus days of retention, SSO and SAML, and audit logs.

At $49 a month, Foglamp is priced for startups, not enterprises, and that is the right call. The bigger observability platforms aimed at LLM teams, like Datadog’s LLM monitoring or the enterprise tiers of tools such as Arize, climb into serious money fast. Langfuse, the closest open-source competitor, is free to self-host but costs you the operational overhead. Foglamp’s pitch is that for less than the price of one bad cost regression, you get managed visibility with almost no setup.

Who is Foglamp Best For?

Use Foglamp if you are a startup or small engineering team shipping AI agents to production and you need to know what they cost and whether they are working, without standing up your own observability stack. The two-line setup and the generous free tier make it trivial to try, and if you build on the Claude Agent SDK it is tuned for you. Anyone who has been surprised by an LLM bill should install it today.

Skip Foglamp if your AI usage is a single occasional API call rather than a real agent in production, because you do not need observability for something that simple. Skip it too if you are a large enterprise with strict data-residency rules and an existing observability platform you must standardize on, in which case the custom tier conversation is the right path rather than the self-serve plans. And if you would rather own and self-host everything, an open-source tool may suit you better.

Best Foglamp Alternatives

Langfuse is the leading open-source LLM observability tool. It is powerful and free to self-host, with a cloud option too, but you trade Foglamp’s near-zero setup for more configuration and operational work. Choose it when you want full ownership of your data.

LangSmith is the observability and eval platform from the LangChain team. It is mature and deeply integrated if you already build on LangChain, with a free tier and paid plans from around $39 per user per month. It is a natural fit for LangChain shops specifically.

Helicone is a lightweight, developer-friendly option that proxies your LLM calls to capture cost and latency with one line of setup. It is simple and has a free tier, though it is lighter on the deep eval and agent-tracing side than Foglamp.

Final Verdict: Is Foglamp Worth It?

Foglamp does one important job and does it with very little friction. The two-line setup, the genuinely useful free tier, and the focus on cost, traces, evals, and alerts make it an easy tool to adopt and a hard one to regret. For any team putting AI agents in front of real users, flying blind on cost and quality is a liability, and Foglamp removes it for $49 a month.

The honest reservations are about maturity and lock-in rather than the product itself. It is a young tool from a small team, so the ecosystem and integrations will keep growing, and teams with heavy data-governance needs will want to talk to them before committing. But for the startup shipping agents this quarter, Foglamp is one of the cleanest ways to get visibility fast, and the free tier means there is almost no reason not to try it. Recommended.