Compare
They all start after the build. Faultmap starts before.
The eval and observability stack needs a running agent and real traces. Faultmap needs only your goal, personas, data, and tools. See the difference, tool by tool.
Before you build · Faultmap
Needs only the goal and the context. Maps the break while changing the design is still cheap.
After you build · every tool below
Needs a running agent, traces, and production telemetry before it can tell you anything.
Tool by tool
You already use one of these. We come one step before them.
Three ways the market attacks agent cost and reliability. We prove the architecture before the build — the step that makes the other two work.
Model routers
Not Diamond, Martian — pick a cheaper model at runtime. Good technique, but nothing proves the task still succeeds.
Eval & observability
LangSmith, Braintrust, Galileo — test after you build. They need a running agent and real traces first.
Building it yourself
The build-then-fix tax: labour, unvalidated spend, and production firefighting — the cost math below.
vsFaultmap vs LangSmith
LangSmith reads the runs. Faultmap reads the goal, personas, data, and tools, and maps the breaks before the first run exists.
See the comparisonvsFaultmap vs Galileo
Galileo guards the running agent. Faultmap maps where it will break in the design phase, before there is anything to guard.
See the comparisonvsFaultmap vs Patronus
Patronus scores the agent you built. Faultmap hands you the first test suite to build against, before you write it.
See the comparisonvsFaultmap vs Braintrust
Braintrust compares versions you built. Faultmap finds the failure modes before version one exists.
See the comparisonvsFaultmap vs Arize
Arize watches production. Faultmap maps the break before the agent ever reaches production.
See the comparisonvsFaultmap vs Helicone
Helicone logs the calls. Faultmap maps the calls that will break before the agent makes one.
See the comparisonvsFaultmap vs Langfuse
Langfuse traces the runs. Faultmap maps the runs that will break before the first one exists.
See the comparisonvsFaultmap vs Datadog
Datadog watches the system you shipped. Faultmap maps the breaks before there is a system to watch.
See the comparisonvsFaultmap vs Weights & Biases
Weights & Biases compares the runs you built. Faultmap names the failures before run one.
See the comparisonvsFaultmap vs Not Diamond
Not Diamond picks the cheaper model after the agent exists. Faultmap maps where the agent breaks before the build — routing is one technique inside the right-sized architecture, the proof is the product.
See the comparisonvsFaultmap vs Martian
Martian optimises the cost of calls you already make. Faultmap proves the architecture holds before the first call exists — so the routing has something safe to route.
See the comparisonvsFaultmap vs Google Vertex AI Agent Builder
Vertex AI Agent Builder gives you the infrastructure to construct and run the agent. Faultmap maps where that agent will break before you commit to building it.
See the comparisonvsFaultmap vs OpenAI Agents SDK
The OpenAI Agents SDK scaffolds how your agents communicate and act. Faultmap maps where those agents will break before the first instruction is written.
See the comparisonvsFaultmap vs Claude Agent SDK
The Claude Agent SDK gives you the runtime to build and run Claude agents. Faultmap maps where those agents will break before you write the first tool.
See the comparisonvsFaultmap vs LangChain
LangChain gives you the wiring to construct the agent. Faultmap maps where the agent will break before you write the first chain.
See the comparisonvsFaultmap vs CrewAI
CrewAI defines who does what inside the crew. Faultmap maps what breaks in the crew's design before any agent runs a task.
See the comparisonvsFaultmap vs LlamaIndex
LlamaIndex builds the retrieval layer and the agent workflows over your data. Faultmap maps where those workflows will break before the first document is indexed.
See the comparisonVs building it yourself — the year-one bill for one agent
Build labour (engineer time)
$55–110K
one agent, before it works
Run cost on unvalidated frontier paths
$150–600+ / 1K requests
biggest model on every call
Fixing what breaks in production
$20–100K / year
retry spirals, silent success, cost runaway
Pavamana production plan
$10K / year
three agents built, validated, kept cost-efficient
Approximate figures from public pricing and typical production workloads (Aug 2026); actual costs vary by workload, model, region, and provider terms.
We are not a replacement. We are the step before them.
Map where yours breaks first. Your first 20 validation tests are free. No card, no code, no traces.