SysMap

AI system planning

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AI system planning for cloud teams

Design the system, price the stack, and let the AI rewrite it cheaper.

SysMap turns a natural-language system brief into an editable architecture map with grounded monthly cost estimates, optimization suggestions, revision history, and exportable diagrams.

Checking API
Structured Gemini output/React Flow workspace/Grounded pricing archive

Live workspace preview

Realtime analytics system

$61/mo after optimize

System brief

Multi-tenant dashboard app with Next.js frontend, API runtime, Postgres, Redis, and object storage.

Generate diagram
Optimize stack
Save revision

Next.js app

Vercel Hobby

API runtime

Cloudflare Workers

Postgres

Neon Launch

Redis cache

Upstash Pay as you go

Object storage

Cloudflare R2

Cost summary

Current$109
Optimized$61
Savings$48

Confidence

3 grounded nodes
1 heuristic node
0 manual overrides

Optimization-aware

Version every rewrite

Pricing confidence

Grounded / heuristic / manual

Provider coverage

Curated archive-backed offers

Current provider set

HetznerNeonUpstashDigitalOcean
CloudflareVercelRenderSupabase

Workflow

One workspace for architecture intent, cloud pricing, and optimization.

The product is designed for teams that want a believable infrastructure planning loop, not a text-only suggestion engine.

01

Describe the architecture

Write what you are trying to ship in plain English and capture assumptions like region, scale, or latency goals.

02

Generate a working graph

Gemini returns a structured topology, then the server lays it out and maps it to real service nodes and edges.

03

Ground the monthly cost

Pricing is resolved against curated provider offers and pricing-page archives instead of pretending every estimate is exact.

04

Optimize and version

Run a rewrite pass, compare savings, and restore earlier revisions if the optimization changes too much.

Product proof

Built around the working surface, not around a chat transcript.

The core UI is an operational builder: prompt input on the left, the map in the center, and pricing plus config on the right. That keeps generation, editing, and review in the same decision loop.

Grounded pricing before confident copy

Nodes are repriced server-side against a deterministic catalog after every AI generation or optimization.

Optimization with revision safety

Every rewrite is saved as a revision so cost savings never mean losing the original architecture.

Explicit confidence states

Each service is marked grounded, heuristic, or manual so the team can see where certainty stops.

AI command surface

Event-driven app with SSR frontend, API workers, managed Postgres, Redis cache, and low-cost object storage.
Realtime analytics stack
Low-cost internal tool
API + data platform

Graph canvas

$84/mo before optimization

Frontend

Vercel

Runtime

Cloudflare

Database

Neon

Cache

Upstash

Storage

R2

Inspector

Node pricing

Neon Launch, us-east-1, 40 GB storage, grounded from curated pricing.

Optimization delta

Switch cache from DigitalOcean managed Redis to Upstash to save $48/mo.

Ready to model the stack

Move from rough architecture notes to a versioned, priced system map.

Start in the workspace, generate the first draft, refine the services, and let the optimizer propose a cheaper version you can actually compare.