The control plane for production AI systems.

Build, run, evaluate, and secure SLMs, RAG pipelines, and AI agents. Continuous evaluation, real-time observability, and policy enforcement—all in one platform.

Trace Timeline
Total: 252ms$0.0023
1
Prompt12ms
2
Retrieval45ms
3
Tool Call128ms
4
Output67ms
4
Steps
252ms
Latency
100%
Success

Integrates with your existing stack

Confluence
SharePoint
Slack
Snowflake
Okta
Datadog

The Challenge

Production AI is hard to trust

Teams shipping AI face the same problems over and over—and most tools don't help.

Silent regressions

Prompt or model updates break production flows without warning. You only find out when users complain.

Stale or unauthorized content

RAG pipelines retrieve outdated documents or expose data users shouldn't access.

Unsafe agent actions

Agents misuse tools, execute unintended operations, or bypass safety guardrails.

Unpredictable token costs

Spending spikes without visibility into which queries or users are driving consumption.

Hard to audit

When something goes wrong, reconstructing 'what happened' requires stitching logs across systems.

Enterprise AI Runtime & Control Plane

Build. Run. Evaluate. Trust.

A unified platform that covers the full lifecycle of production AI systems.

Models

  • SLMs, LLMs, embeddings
  • Version & prompt management

Context

RAG / MCP

  • Retrieval pipelines
  • Tool & data connectors

Agents

  • Multi-step orchestration
  • Tool use & planning

Evals

  • Continuous testing
  • Regression detection

Observability & Safety

  • Real-time tracing
  • Policy enforcement

From model deployment to production monitoring—one control plane for your entire AI stack.

Platform Pillars

Five pillars of production AI

A complete stack for building, running, and trusting AI in production.

SLM Factory

Fine-tune, distill, and serve small language models optimized for your domain.

  • Custom fine-tuning pipelines
  • Model distillation
  • Low-latency serving

RAG + MCP Connectors

Permissioned context retrieval with enterprise data source integrations.

  • Access-controlled retrieval
  • MCP protocol support
  • Real-time sync

Agent Runtime

Deterministic execution graphs with human-in-the-loop checkpoints.

  • DAG-based orchestration
  • HITL approval gates
  • Rollback & replay

Continuous Evaluation

Offline and online evals with automated regression gates before deploy.

  • Benchmark suites
  • Shadow testing
  • Regression blocking

Observability & Safety

Full-stack tracing, cost attribution, PII detection, and audit logs.

  • Distributed traces
  • Policy enforcement
  • Compliance audit trail

Process

How it works

Four steps to production-grade AI you can trust.

01

Instrument

SDK traces

  • Drop-in SDKs for Python, TypeScript, and REST
  • Auto-capture prompts, completions, latency, and cost
02

Govern context

RAG permissions + MCP tools

  • Define who can access which data sources
  • Register and version MCP tools with schemas
03

Execute safely

Agent policies + approvals

  • Set guardrails for tool calls and outputs
  • Route high-risk actions to human approval queues
04

Evaluate & improve

Continuous eval + rollback

  • Run evals on every deploy with regression gates
  • One-click rollback to last known good version

Ecosystem

Connects to your stack

Out-of-the-box integrations for data sources, tools, models, and observability.

Data Sources

ConfluenceWiki & docs
SharePointEnterprise files
NotionTeam workspace
Google DriveCloud storage
SnowflakeData warehouse
PostgreSQLRelational DB

Tools

SlackTeam messaging
JiraIssue tracking
GitHubCode & PRs
LinearProject mgmt
ZendeskSupport tickets
SalesforceCRM data

Models

OpenAIGPT-4, embeddings
AnthropicClaude models
Azure OpenAIEnterprise GPT
CohereEmbed & rerank
MistralOpen models
Custom SLMsYour fine-tunes

Observability / SIEM

DatadogAPM & logs
SplunkSIEM & search
GrafanaDashboards
PagerDutyIncident mgmt
OktaIdentity & SSO
WebhookCustom events
50+ integrationsCustom connectors via MCP protocol

Trust & Compliance

Security and compliance by design.

We built security into every layer—from data ingestion to model output. Your AI systems stay protected, auditable, and compliant.

SOC 2 Type IIGDPRHIPAA ReadyISO 27001

SSO/SAML + RBAC

Enterprise identity with fine-grained role-based access control.

Encryption in transit & at rest

TLS 1.3 for all connections, AES-256 for stored data.

Immutable audit logs

Tamper-proof records of every action for compliance and forensics.

PII detection & redaction

Automatic scanning and masking of sensitive data in prompts and outputs.

Prompt injection defenses

Input validation and guardrails to protect RAG pipelines from attacks.

VPC / on-prem options

Deploy in your own infrastructure for maximum data sovereignty.

Pricing

Plans for every stage

From early exploration to regulated enterprise deployments.

Team

Best for: Startups and small teams exploring AI in production

  • Up to 10 team members
  • Core tracing & observability
  • Basic eval framework
  • Community integrations
  • Standard support
  • 7-day log retention
Most Popular

Enterprise

Best for: Scaling teams with production AI workloads

  • Unlimited team members
  • Advanced tracing & cost attribution
  • Continuous eval with regression gates
  • SSO/SAML + RBAC
  • Priority support & SLAs
  • 90-day log retention
  • Custom integrations
  • Dedicated success manager

Regulated

Best for: Healthcare, finance, and government with strict compliance

  • Everything in Enterprise
  • HIPAA BAA available
  • VPC / on-prem deployment
  • Immutable audit logs
  • PII detection & redaction
  • Custom data residency
  • Dedicated infrastructure
  • 24/7 premium support

FAQ

Frequently asked questions

Common questions about the platform, deployment, and security.

Yes. We support OpenAI, Anthropic, Azure OpenAI, Cohere, Mistral, and any model accessible via API. You can also bring your own fine-tuned SLMs. Switching models requires no code changes—just update your configuration.
Yes. Our Regulated tier includes full on-premises deployment with air-gapped licensing. We also offer VPC deployment for Enterprise customers who need network isolation without managing infrastructure.
You define eval suites with custom or built-in evaluators (accuracy, latency, cost, safety). Evals run automatically on every deploy. If metrics regress beyond thresholds you set, the deploy is blocked until reviewed. Shadow testing lets you compare new versions against production before switching.
Team plans retain logs for 7 days. Enterprise retains for 90 days. Regulated plans support 1+ year retention with immutable audit logs. You can configure custom retention per data type and export logs to your own storage at any time.
Yes. We support real-time streaming to Splunk, Datadog, and any SIEM that accepts webhooks or syslog. Security events, access logs, and policy violations can all be routed to your existing security infrastructure.
Each data source connector inherits permissions from your identity provider (Okta, Azure AD, etc.). When a user queries RAG, we enforce row-level and document-level access based on their identity. Admins can also define explicit allow/deny rules per connector.

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