Przestań płacić sztucznej inteligencji za czytanie.
Niech zapyta SMART TS XL.
Obniż rachunek.
Twoja sztuczna inteligencja już czyta Twój kod. Dzięki SMART TS XL odczytuje odpowiedź, a nie całe repozytorium.
Even a conservative 20% saves $200 million every six months. Large banks can save hundreds of millions of dollars a year.
On every $1 billion of AI code-analysis spend
Same AI. Same questions. Smaller bill.
Every question your AI answers about your code costs money. The difference is how much code it has to read to get there.
The AI reads, and reads again
- Searches raw files and re-reads code for every question
- Wades through noise: one plain text search for a common COBOL word returned 61,417 matches
- Rebuilds the same understanding in every session, and pays for it every time
The AI asks, and gets the answer
- Gets the exact lines and relationships, already analyzed
- jeden SMART TS XL search covered 131,212 documents in 0.31 seconds
- Works with ChatGPT, Claude, Copilot, Gemini and Grok. Your code stays on your servers
See how the savings happen
A 2.5-minute explainer, and a one-minute film about the AI bill.
See your AI bill shrink.
Pick a company size or move the sliders.
W naszych testach
Real prompts run on IN-COM’s demo system, with SMART TS XL and without it.
Overnight test
All 4 finished.
Finishing: an estimated $295–$538 and about 13 hours.
One hard question
Done, with complexity and cross-reference reports.
Stopped after 4 of 529 files.
Dokumenty 131,212
One search, exact lines returned.
The AI opens and reads files one at a time.
One common COBOL word
Only the lines asked for.
From a plain text search, for the AI to read through.
What would you ask your code?
Type a question your teams ask today. We’ll show the closest real example, and run yours on real code in a live session.
Stop paying AI to read. Let it ask SMART TS XL. Cut your bill.
See what you’d save, measured on your own code.
Sources for AI spend levels (2026, publicly reported): Typical: Anthropic, Claude Code cost documentation, average about $13 per developer per active day, $150–250 per month (code.claude.com). Heavy: Uber and Microsoft power users at $500–2,000 per engineer per month; Uber cap of $1,500 per engineer, per month, per tool (Forbes, Zjednoczyć.AI). Agentic: top 1% of AI-adopting companies at about $7,500 per employee per month, Ramp AI Index (Zjednoczyć.AI); Meta about $50,000 per employee per year at list prices, SemiAnalysis (Crypto Briefing). Frontier: StrongDM guideline of $1,000 per engineer per day; 16 parallel agents at about $20,000 over two weeks, about $1,400 per agent-day, used for automated AI jobs (The Emerging Token Gap). Major bank: an IN-COM conversation with a bank spending about $1 billion every six months on AI code analysis; the bank is not named. Lines-of-code effects (up to 2x per-developer spend; about 2.8 automated AI jobs per million lines, calibrated to the bank example) and savings levels (20% / 40% / over 60%) are IN-COM estimates. Test results are from IN-COM’s demo system. All figures are estimates for illustration only, not a quote or guarantee; actual costs and savings vary by organization, tools, models and usage.
