AI tool comparison
Kampala vs LiteRT-LM
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Kampala
MITM proxy that reverse-engineers any app into a stable, callable API
75%
Panel ship
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Community
Free
Entry
Kampala, built by Zatanna AI (YC W26), is a macOS proxy tool that sits between your applications and the internet, intercepts every HTTP/HTTPS request, and automatically reverse-engineers the underlying API. It traces authentication chains — tracking tokens, cookies, and session state — and replays flows on demand, preserving original TLS fingerprints so services can't distinguish API calls from the real app. The key insight is that almost every app that lacks a public API still has a private one — and it's usually more stable than the UI. Kampala targets automation engineers, QA teams, and AI agent builders who need reliable machine-readable access to apps that haven't opened their APIs. Setup is a local MITM cert install; no cloud proxy involved. Currently macOS-only with a Windows waitlist. The team emerged from YC's Winter 2026 batch with backing from Y Combinator. Pricing is in early access, with a free tier planned for solo developers and paid plans for teams building production automations.
Developer Tools
LiteRT-LM
Run Gemma 4 and other LLMs fully on-device — no cloud required
75%
Panel ship
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Community
Paid
Entry
LiteRT-LM is Google's production-grade, open-source inference framework for deploying Large Language Models on edge devices — phones, IoT hardware, Raspberry Pi, and desktop machines without cloud connectivity. Launched April 7, 2026 alongside Gemma 4 support, it enables developers to run Gemma, Llama, Phi-4, Qwen, and other models entirely locally via a simple CLI or embedded SDK. The framework handles the hard parts of edge inference: memory-mapped per-layer embeddings, 2-bit and 4-bit quantization, NPU acceleration for Qualcomm and MediaTek chipsets (early access), and cross-platform support spanning Android, iOS, Web, and desktop. Gemma 4's E2B variant runs under 1.5GB RAM on some devices, making full LLM functionality viable on mid-range hardware. What makes LiteRT-LM significant is the agentic angle. It's one of the first frameworks to support multi-step agentic workflows running completely on-device — function calling, tool use, vision and audio inputs — without a single network request. For developers building privacy-sensitive apps or offline-capable agents, this changes the calculus entirely.
Reviewer scorecard
“This is the tool I've been building in-house at three different companies and never had time to productize properly. The auth chain tracing alone — tracking token refresh flows and session state automatically — would have saved me hundreds of hours. If it works as advertised, it's an instant ship for anyone doing integration work.”
“This is the real deal for edge AI development. The CLI makes it trivial to get Gemma 4 running locally in minutes, and function calling support means you can build actual agentic apps that work offline. Google backing means this won't be abandoned in six months.”
“Terms of service violations are a real concern here. Most apps explicitly prohibit automated access through their private APIs, and companies like LinkedIn and Instagram have sued over exactly this pattern. The MITM cert requirement also opens a broad attack surface. Wait for a clearer legal stance before building production systems on this.”
“NPU acceleration is still early access and the model selection is Google-heavy. Developers building with Llama or Mistral have Ollama and llama.cpp with far more mature ecosystems. LiteRT-LM needs a year of community baking before it rivals those alternatives.”
“The long-term story here is about AI agents needing reliable access to every app humans use. We can't wait for every SaaS to ship an official API. Tools like Kampala are how AI agents will integrate with the existing software ecosystem for the next five years, until MCP-style universal interfaces catch up.”
“On-device agentic AI is the privacy-preserving future of personal computing. LiteRT-LM gives Google a strong position in edge inference infrastructure — expect this to become the default runtime for Android AI features within 18 months.”
“For social media automation and cross-platform content workflows this is a game-changer. Building automations for platforms with limited or expensive APIs has always required fragile browser scraping — having a stable API layer extracted from the real app traffic is a much better foundation.”
“The vision and audio input support unlocks real creative tools that work on a plane or in a studio without WiFi. Running a multimodal model locally with no usage fees means I can experiment with AI-assisted workflows without watching a billing meter.”
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