Why We Built SynapseKit: The Truth About Production LLM Frameworks | by EngineersOfAI | May, 2026 | MediumSitemapOpen in appSign up<br>Sign in
Medium Logo
Get app<br>Write
Search
Sign up<br>Sign in
Why We Built SynapseKit: The Truth About Production LLM Frameworks
EngineersOfAI
8 min read·<br>12 hours ago
Listen
Share
How we learned that 2 dependencies beat 50+, async-first beats sync-bolted-on, and transparency beats SaaS lock-in. The story of building an LLM framework from first principles.
Read the full article with interactive visualizations on engineersofai.com .<br>Git : https://github.com/SynapseKit/SynapseKit<br>Doc :https://synapsekit.github.io/synapsekit-docs/<br>The Problem We Lived<br>Imagine a scenario at 3 AM. Production on fire. An LLM pipeline cold-started on Lambda, and the container was taking 30 seconds just to import dependencies. Meanwhile, the observability tool you paid $99/month for was telling you… nothing useful.<br>You’d chosen a popular framework because it was the “safe” choice. It had 100K stars, enterprise support, and a massive ecosystem. But in production, it felt like you were fighting the framework as much as building with it.<br>The async APIs were baked on top of synchronous code. The dependency tree was a forest (50+ transitive deps). Observability required another SaaS subscription. And debugging? Forget it too much “magic” between you and the LLM call.<br>You’re not unique. Thousands of teams have hit the same wall. And we thought: What if we rebuilt this from first principles?<br>That question became SynapseKit.<br>What SynapseKit Actually Is<br>SynapseKit is not trying to be a LangChain killer. It’s trying to be different.<br>The difference starts here — not features, but principles :<br>| Problem | LangChain-Style | SynapseKit |<br>| --- | --- | --- |<br>| Dependencies | 50+ (200 MB) | 2 (numpy, rank-bm25) |<br>| --- | --- | --- |<br>| Async Design | Bolted on | Native from day 1 |<br>| Cost Visibility | $99+/month SaaS | Built-in, free |<br>| Deployment Tools | Deprecated | synapsekit serve |<br>| Observability | Black box | Instrumented, transparent |<br>| Token Tracking | Hidden | Per-call tracking |We’re building for production teams who are tired of choosing between:<br>Power (but complexity)<br>Simplicity (but missing features)<br>Open source (but no support)<br>Commercial (but expensive and lock-in<br>SynapseKit says: You don’t have to choose.<br>What This Means for You<br>1. You Own Your Code<br>Every LLM call, every prompt, every decision — it’s yours. There’s no proprietary “chain” abstraction hiding what’s happening.<br>from synapsekit import RAG
rag = RAG(model="gpt-4o")<br>rag.add("Your documents")<br># This actually does what you think it does.<br># No hidden orchestration. No vendor-specific magic.<br>result = await rag.query("What is this about?")Compare to frameworks where rag.query() invokes 12 internal transformations you didn't ask for.<br>2. You Keep 90% of Your Cold Start<br>Lambda cold starts matter. A 2 KB framework matters.<br>We measured: import synapsekit = 200 ms. import langchain = 2.8 seconds.<br>That’s not hypothetical. That’s real deployments. That’s the difference between your API responding in 100 ms vs 3 seconds during scale events.<br>3. You See Your Costs<br>from synapsekit import CostTracker, BudgetGuard<br>tracker = CostTracker()<br>guard = BudgetGuard(daily=10.0, per_request=0.50)<br>with tracker.scope("my_pipeline"):<br>result = await rag.query("Question?")<br>print(tracker.summary())<br># Output:<br># total_cost: $0.0234<br># tokens_in: 1,200<br># tokens_out: 450<br># model: gpt-4o<br># cost_per_1k: $2.50 / $15.00Every LLM framework should have this. No SaaS fees. No surprise bills. Just facts .<br>Why We’re Staying Open Source (Forever)<br>This matters. So let’s be clear about what open source means to us.<br>The Temptation<br>VC-backed frameworks always face the moment: “When do we monetize?”<br>LangChain took it by building LangSmith ($99+/mo). That’s a valid business model. But it creates incentive misalignment: the best features live behind a paywall.<br>We’re choosing differently.<br>The Bet<br>SynapseKit core = Apache 2.0 forever.<br>No tricky license changes. No “open core” where the good stuff is closed. No “we’re keeping the best for enterprise.”<br>The framework you use in production is the same framework available to students, hobbyists, and competitors.<br>Why? Because:<br>Trust compounds.<br>Bugs matter less.<br>Optimization flows both ways.<br>We make money differently.<br>What We Monetize<br>We monetize on top, not instead of:<br>SynapseKit Core<br>EvalCI Pro<br>synapsekit.cloud<br>Compliance reports<br>The core framework is the funnel. Everything else is optional.<br>This is the bet: Build the most trustworthy LLM framework. Let it be free. Earn money by solving operational problems the framework surfaces.<br>What the Community Taught Us<br>We shipped SynapseKit in March 2026. By May, we had 19 contributors and 9,200 downloads in 30 days. 13,000 downloads now and counting.<br>Here’s what the community actually cares about (not what we thought they would):<br>Simplicity Beats Ecosystem<br>We expected people to love our 33 LLM providers....