Slow software costs money. Let us fix it.
Diagnosis and optimization of applications with real bottlenecks — database, cache, code, or infrastructure. Measurable result, not just a report.
write performance
The sales-reporting module of a European retail SaaS got slower as report ranges grew (month → quarter → semester), with latency bleeding into inserts and internal services. Jaeger profiling + a UUID v4 to v7 migration across distributed databases (billions of records) with a custom Rust tool. Result: +260% write performance. A full Go rewrite was avoided.
The problem we solve
LCP above 3s, queries that stall production, APIs with an 8-second P99. Performance issues are accepted as normal until the day they stop the business — and on that day, people often react with the most expensive decision possible: rewrite everything.
In most cases, the rewrite is unnecessary. We have seen the sales-reporting module of a European retail SaaS consider a full migration to Go when the real cause was index fragmentation from random UUIDs across distributed databases. Slow software almost always has three to five concrete causes, not a "need to switch languages."
How we work
Real production profiling (not dev, where the numbers lie), identification of the 3-5 causes that explain 80% of the problem, and a surgical fix with before/after benchmarks. No unnecessary rewrite.
The work usually starts at the database, where most bottlenecks live: EXPLAIN ANALYZE on the slowest queries, index review, hunting N+1s in the ORM, and distributed tracing (Jaeger) to see where the latency really originates. Then session and auth caching, payload size in API responses, an undersized connection pool, and assets without compression or a CDN. The UUID v4 → v7 case is emblematic: in the sales-reporting module of a European retail SaaS, reports got slower as the range grew (month → quarter → semester) and the latency bled into inserts and internal services. The cause was index fragmentation from random keys across distributed databases. Swapping key generation for a time-ordered one — migrating billions of records with a custom Rust tool — returned +260% write performance and made the full Go rewrite under consideration unnecessary.
Every change ships to production carefully: benchmarked, with rollback prepared, applied at a low-traffic window when possible. The deliverable is not a pretty report — it is a verifiable before-and-after comparison.
Before rewriting, check
- Indexes used in the slowest queries (EXPLAIN ANALYZE).
- N+1 queries in the ORM.
- Session and auth caching.
- Payload size in API responses.
- Connection pool properly configured.
- Uncompressed assets or no CDN.
Have a slow application that is costing customers or money?
Describe the symptom — we respond with the right questions to diagnose.
- Real production profiling, not a dev environment
- Identification of the 3-5 causes that explain 80% of the problem
- EXPLAIN ANALYZE on the slowest queries and index review
- Hunting N+1s, bloated payloads, and a misconfigured connection pool
- Surgical fix with rollback prepared and a low-traffic window
- Before/after benchmark delivered as a verifiable comparison
Investment ranges
Micro Project
PoC, institutional site, WhatsApp and small chatbots. Non-regulated sector, or your first AI project.
$8,000 – $20,000
- Delivery in weeks
- RAG + light harness
Small Project
Well-defined scope: targeted automation, lean MVP, focused integration.
$20,000 – $70,000
- Fixed scope
- Delivery in weeks
Medium Project
RAG chatbot, enterprise AI agent, SaaS MVP, performance execution.
$70,000 – $220,000
- Dedicated architecture
- Integrations
Large Project
Legacy modernization, system rewrite, multi-phase transformation.
From $230,000
- Multiple phases
- Dedicated team
Qualitative ranges. The exact figure comes out of Discovery, and is 100% credited toward the project.
FAQ
Do you touch production systems?
Yes, carefully. Every change is benchmarked, rollback is prepared, and we deploy at low-traffic windows when possible.
How long until we see results?
Depends on the problem. Quick wins (index, cache) show up in hours. Larger refactors take 1-3 weeks. We always deliver a comparative benchmark.
Does it work with any stack?
Yes. Node.js, Go, Python, Ruby — the bottleneck is usually in the database or business logic, not the language.
How much does a performance engagement cost?
Quick wins are short in scope; deeper refactors are scoped as a project. We estimate a qualitative range from the diagnosis, credited if the work moves forward.