The full-stack layer for production agents

Vektor provides every primitive your team needs to evaluate, observe, and scale AI agents — from prototype to billions of interactions.

01

Evaluations

Automated quality gates for every agent release

Define custom scorers, run LLM-as-judge evaluations, and integrate pass/fail checks into your CI pipeline. Supports chain-of-thought scoring, tool-call validation, and behavioral regression detection.

  • →40+ pre-built scorers covering safety, faithfulness, and tone
  • →Custom rubrics via natural language or Python
  • →Per-trace, per-deploy, and shadow eval modes
  • →Pass/fail blocking gates wired into GitHub, GitLab, and Buildkite
LLM-as-judgeRegression detectionCI integration
02

Tracing

Full-span observability from input to output

Auto-instrument agents built on any framework. Capture LLM calls, retrieval steps, tool invocations, and memory operations. Reconstruct full execution DAGs in the dashboard.

  • →Zero-config auto-instrumentation across 12 popular frameworks
  • →DAG visualization with token, latency, and cost overlays
  • →Replay any span with a swapped model or prompt
  • →Native OpenTelemetry export to Datadog, Honeycomb, and S3
OpenTelemetryLangChainLlamaIndexCrewAI
03

Memory

Persistent context that agents actually remember

Give agents episodic, semantic, and procedural memory stores. Vektor handles chunking, embedding, retrieval scoring, and selective compression so your agent stays on task.

  • →Three first-class stores: episodic, semantic, procedural
  • →Automatic chunking, embedding, and re-ranking
  • →Selective compression preserves salient facts over 100k+ turns
  • →Drop-in compatible with Pinecone, Weaviate, and pgvector
EpisodicSemanticProceduralRAG-compatible
1.4B+
Traces ingested last quarter
200+
Enterprise teams in production
99.99%
Control plane uptime, T12M
SOC 2 II
Audited, with HIPAA add-on

What teams build on Vektor

Customer support agents

Block regressions in tone and policy adherence before they reach end users. Replay every escalation with a different model in one click.

62% lower escalation rate

Coding & dev-tools agents

Score generated diffs against test suites, lint rules, and reviewer rubrics. Catch silent capability drops when you swap model versions.

4.1× faster release cadence

Sales & GTM agents

Audit outbound copy, qualification logic, and CRM writes. Pair every trace with the eventual booked-meeting outcome.

2.3× pipeline per SDR-hour

Internal research copilots

Long-horizon memory across thousands of documents, with citation-aware retrieval that survives context window resets.

94% citation precision

Vektor speaks OpenTelemetry, so anything that emits OTLP works out of the box. We ship first-class SDKs and zero-config tracers for the frameworks below.

LangChain
LlamaIndex
CrewAI
AutoGen
Vercel AI
OpenAI
Anthropic
Gemini
Mistral
Pinecone
Weaviate
pgvector

Common questions before you start

Do I need to rewrite my agent to use Vektor?

No. Vektor wraps any function — pure Python, LangChain, LlamaIndex, CrewAI, AutoGen, plain OpenAI/Anthropic SDK calls. Three lines of SDK code instrument an existing agent.

How does pricing work?

Free up to 50,000 traces per month. Above that, pay per ingested span with volume discounts. Evaluations and Memory are priced separately so you only pay for what you use.

Where is my data stored?

US, EU, and APAC regions. Bring-your-own-bucket is available on the Enterprise plan, including S3 and GCS. Spans never leave your selected region.

Can Vektor run on-prem or in a VPC?

Yes. We ship a single-binary control plane plus a Helm chart for the data plane. Air-gapped installs are supported for design-partner enterprise customers.

Ship agents your CTO would deploy on a Friday

Free tier up to 50K traces / month. No credit card. SOC 2 Type II audited.