Real agents need more than single-turn evals.

Multi-turn, multi-tool, open source. Yours to extend.

Humanloop scores single input/output pairs through a closed platform. LangWatch is OpenTelemetry-native, simulates full multi-turn agent flows, and gives you the source code under Apache 2.0.

Join thousands of AI developers shipping reliable agents with LangWatch.

single-turn eval
input: refund query
output: refund flow
score: 0.84
looks fine? not the whole story.
multi-turn simulation
turn-01 · greet
turn-02 · classify
turn-03 · lookup
turn-04 · policy ❗
turn-05 · escalate
caught at turn-04
turns/run
12
tools called
4
open source
yes
The Humanloop alternative.

How LangWatch compares to Humanloop.

Five things teams care about when picking a quality layer for agents. Each row shows what Humanloop ships today and what LangWatch gives you on day one.

01
Multi-turn testing
Agent simulation suite

Simulate multi-turn, multi-modal conversations with tool use, persistent state, and a configurable virtual user.

Single-turn evaluation

Traditional eval platform focused on single input/output pairs. Multi-step agent flows are not the core model.

02
Source code & deploy
Open source platform

Transparent codebase. Self-host with Docker or Helm. Customize anything. Audit every component.

Proprietary SaaS

Closed-source platform with restricted customization and dependency on vendor-controlled infrastructure.

03
Observability
Native OpenTelemetry

Standardized tracing, metrics, and logging across every supported framework, no extra configuration.

Custom instrumentation

Proprietary SDK integration required, limiting interoperability with existing observability tooling.

04
Evaluator model
Code + UI evaluators

Python and TypeScript APIs for complex logic. UI for domain experts. Both edit the same source of truth.

GUI-led workflows

Platform-centric workflows designed primarily for manual testing and GUI-based configuration.

05
Prompt optimization
DSPy-native automation

Real optimization algorithms that generate, score, and select prompt variants automatically.

Manual prompt management

Prompt versioning and A/B testing capabilities, but optimization decisions still require human intervention.

Three reasons agent teams choose LangWatch.

6 turns · 1 caught
Test the whole agent, not the prompt

Multi-turn simulations exercise tools, state, and reasoning. The kinds of failures that pop in production show up here first.

closed SaaSacquisition riskApache-2.0your repo, your rules
No vendor lock-in

Self-hosted Apache 2.0 deployment removes platform discontinuation risk. Acquisition-proof, by design.

v1 → v8 · score 0.91
DSPy-native optimization

Algorithmic prompt optimization through systematic experimentation. Stop tuning prompts by hand.

Single-turn evals shipped a polite agent that broke on call three. Multi-turn simulations caught it in seven minutes.
Lead engineer · Voice AI agent team
94%
regressions caught pre-prod
5 min
time-to-first-eval
any
frameworks supported
$0
cost to start

Evals are table stakes. Agent simulation is the bar.

Try LangWatch yourself or book time with an expert to help you get set up.