Your AI control layer for the enterprise — Build, Review, Observe, Improve and Secure every model, agent and pipeline in production.
The AI Lifecycle
One continuous loop for shipping enterprise-grade AI with confidence.
Ship AI features faster with a proven foundation.
Catch regressions and risks before they ship.
End-to-end visibility into models, agents and data.
Tune prompts, models and pipelines continuously.
Guard your AI from prompt to production.
Out of the Box Use Cases
From semantic modelling to agentic observability — start with what you need today and scale across the stack.
Unified semantic layer that powers reliable AI on your enterprise data.
Grounded, permission-aware search across every internal source.
Persistent context graph for agents, copilots and knowledge tools.
Production chat experiences with guardrails, memory and analytics.
Trace prompts, tokens, latency and quality across every model call.
Watch multi-step agents in real time and debug failures fast.
Automated code review tuned for AI-generated and AI-assisted PRs.
Retrieval pipelines tuned for accuracy, recall and cost.
Turn production traces into evals and ship with confidence on every release.
A/B test prompts and models side-by-side with quality, cost and latency metrics.
Auto-generate meaningful tests for AI-assisted code across complex repos.
Codify your engineering rules and enforce them on every PR — automatically.
Score live traffic in real time with custom scorers and human review queues.
Design, orchestrate and monitor multi-step agents from prototype to production.
A company-aware assistant that answers questions across every tool and team.
Pre-built connectors for SaaS apps, wikis and data warehouses — permission-aware.
Auto-built graph of people, content and activity that grounds every AI response.
Summarise, classify and extract insights from contracts, tickets and reports.
LLM Gateway
Sit between your agents and any provider. Optimise tokens, manage prompts as code, and route every request to the right model — without changing application code.
Cut spend without sacrificing quality.
Version, evaluate and roll out prompts safely.
Route requests to the best model for the job.
Security
Stop prompt injection, agent abuse and data exfiltration before they reach production.
Policy, identity and runtime defense for autonomous agents.
Block prompt injection, data leakage and unsafe output.
Work With Founders From
Why DataSignals
Real-time insights to slash spend without quality loss.
Evaluation pipelines that catch regressions early.
Trace every AI interaction across your stack.
Faster responses without slowing down teams.
Built-in controls for compliance from day one.
Built for Real-World AI Teams
DataSignals adapts to your stage and stack — from a single AI feature in production to multi-team, multi-region deployments.
What You Can Achieve
Talk to our team about Build, Review, Observe, Improve and Secure — across every model and agent in your enterprise.
Book a Demo