Telmai delivers AI-driven data observability built on an open architecture, so teams can monitor data quality wherever their data lives rather than being locked into a single warehouse or vendor. The platform uses machine learning to profile data and detect anomalies, schema drift, and quality issues across pipelines, data warehouses, and data lakes, alerting teams before bad data propagates into analytics, applications, and AI models. Its no-code, scalable approach is designed to work on both streaming and batch data at high volume, helping data engineers and analysts maintain trust in their data foundations. Telmai raised an oversubscribed $5.5M seed round co-led by Glasswing Ventures and .406 Ventures, with participation from existing investors including Zetta Venture Partners, to expand its AI-driven, open-architecture observability platform.
Telmai
ActiveOpen-architecture, AI-driven data observability
Total raised
$5.5M
1 round
Stage
Seed
Team
11-50
since 2020
Pricing
Freemium
free plan
Founded
2020
Sunnyvale, United States
Agent-ready
API
Score 40/100
AI-driven anomaly detection
Open-architecture deployment
Data quality monitoring across pipelines
Schema drift detection
Streaming and batch data support
No-code configuration
Alerting before downstream impact
Works across warehouses and lakes
40/100
Developing
MCP server
Public API
Webhooks
OAuth 2.0
SDKs
— Seed $5.5M incl. .406 Ventures +2
Capital network
$5.5M raised ·3 backers·10 network links
- Backers3
- Shared portfoliocompanies these backers also fund
- Extended networkfunds that co-invest alongside them
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- What does Telmai monitor?
- Telmai monitors data quality, anomalies, and schema drift across pipelines, warehouses, and data lakes.
- Why open architecture?
- Open architecture lets Telmai observe data wherever it lives without locking teams into a single platform.
- How much has Telmai raised?
- Telmai raised an oversubscribed $5.5M seed round co-led by Glasswing Ventures and .406 Ventures.
- Does Telmai handle streaming data?
- Yes, it supports both streaming and batch data at scale with a no-code setup.
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