AutoInfra, Inc.
Morph builds specialized inference engines and infrastructure (search, edits, compaction) to enable AI coding agents to ship software faster and more accurately.
At a Glance
- AI software engineering agent builders
- Enterprise software teams
- DevTool companies
- AI infrastructure providers
AI Tools by AutoInfra, Inc.
(1)
Morph
LLM Code Merge for AI Agents
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Latest News
Morph Labs raises $5.75M seed round led by Khosla Ventures to build infrastructure for AI software engineering agents.
The Bitter Lesson Applied: Why Coding Agents Need More Compute, Not More Cleverness
Lessons from 40+ Coding Agent Harnesses: Context Is the Entire Game
Flash Compact: 33,000 tok/sec Context Compaction released
Products & Services
Ultra-fast agentic code-search tool ranked #1 on SWE-Bench Pro. Optimized for speed and cost-efficiency compared to traditional search.
High-speed code editing model capable of >10,500 tokens/second, enabling near-instant AI code updates with zero failure rates.
Near-lossless context compaction tool that reduces context window size by 50-70% at 33,000 tokens/second.
AI-driven browser automation for testing Pull Requests directly in GitHub to capture UI bugs before release.
Market Position
Positions itself as the 'fastest inference engine' for code edits, outperforming general LLMs in latency and token throughput (10k+ tok/s). Differentiates by focusing on agentic infrastructure rather than building a standalone coding assistant like Cursor.
Leadership
Founders
Tejas Bhakta
Founder & CEO of Morph (AutoInfra, Inc.). Previously a Computer Vision Engineer at Tesla working on Autopilot AI. Y Combinator S23 alumnus. Born and raised in a hotel.
Executive Team
Tejas Bhakta
Founder & CEO
Ex-Tesla AI engineer with a focus on machine learning infrastructure and computer vision. Lead founder of Morph.
Board of Directors
Founding Story
Tejas Bhakta, an ex-Tesla AI engineer who worked on Autopilot computer vision, founded Morph (AutoInfra) in 2023 to address the slow speed and context limitations of general LLMs when used by coding agents. After joining Y Combinator S23, the company focused on building high-performance infrastructure specifically for agentic code edits and search.
Business Model
Revenue Model
Credits-based subscription and API usage-based pricing.
Pricing Tiers
250K credits, low rate limits.
2M credits, generous rate limits.
8M credits, generous rate limits. (First month $5 promotion).
80M credits, practically no rate limits.
Target Markets
- AI software engineering agent builders
- Enterprise software teams
- DevTool companies
- AI infrastructure providers
- Locating logic in large monorepos
- Instant AI code patching
- Context window optimization for agents
- Automated PR testing
- Enterprise-scale AI coding agent deployment
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