Six blueprints — before the first client case goes public.
Architecture blueprints for six common agents. Each one shows the problem, the agent architecture, the security behaviour and a realistic impact range — based on industry benchmarks, not our own measurements.
NOTE · BLUEPRINT FORMAT
Turivus launched in 2026 — the six use cases below are architecture blueprints, not completed client projects. The impact ranges shown come from published industry benchmarks and comparable implementations, not from our own measurements. We share them so you can see how we frame a problem and where we place the security layer.
Support Agent
Reads, classifies, and answers support emails automatically.
Typical SME problem
200+ support emails per day. Manually processed. Slow, expensive, inconsistent.
Agent architecture
Agent reads emails, classifies (bug/feature/question), auto-responds to standard inquiries, escalates complex ones to the right specialist.
Security behaviour
Customer data (email, account ID) is masked before it reaches the AI. Only the Security Layer knows the real identities.
Expected impact range
Based on industry benchmarks, not Turivus measurements.
60%
Auto-Response Rate
2h → 5 min
First Reply Time
-40%
Support Costs
+15%
Customer Satisfaction
Finance Agent
Automatically checks invoices against purchase orders.
Typical SME problem
500+ invoices/month. Manual matching with POs. 5-7 day cycle time. Many errors.
Agent architecture
Agent reads invoices (OCR), matches with orders, checks amounts, approves standard cases, flags deviations.
Security behaviour
Banking data and amounts are only processed locally (local LLM). No financial data leaves the company.
Expected impact range
Based on industry benchmarks, not Turivus measurements.
80%
Auto-Approval
5 days → 24h
Cycle Time
5% → <0.5%
Error Rate
6h → 1h/day
Manual Work
Sales Agent
Qualifies leads automatically and sends outreach.
Typical SME problem
300+ leads/month. Sales team qualifies manually. 40% of time spent on low-quality leads.
Agent architecture
Agent researches companies automatically, scores against Ideal Customer Profile, sends personalized outreach emails, tracks responses.
Security behaviour
Lead data (personal info) is masked internally. Only anonymized company data goes to the AI for research.
Expected impact range
Based on industry benchmarks, not Turivus measurements.
15 min → 2 min
Qualification Time
+50%
Close Rate
+30%
Sales Productivity
-50%
Cost per Lead
HR Agent
Screens CVs and ranks candidates automatically.
Typical SME problem
500+ CVs/year. HR screens 20h/week manually. Good candidates slip through.
Agent architecture
Agent screens CVs against job description, extracts skills, ranks candidates (green/yellow/red), sends interview links automatically.
Security behaviour
CVs contain highly sensitive data (name, address, photo). Only anonymized skills and experience go to the AI. Local LLM mandatory.
Expected impact range
Based on industry benchmarks, not Turivus measurements.
10 min → 30s
Screening Time
40% → 55%
Interview Conversion
15h/week
HR Time Saved
Consistent
Evaluation
IT Ops Agent
Filters alert noise and diagnoses root cause.
Typical SME problem
100+ system alerts/day. Alert fatigue. Important issues are overlooked. MTTR: 4h.
Agent architecture
Agent filters noise, diagnoses root cause, prioritizes (P1/P2/P3), attempts self-healing, escalates when necessary.
Security behaviour
System alerts contain server names, IPs, configurations. Analysis happens locally only. No infrastructure data in the cloud.
Expected impact range
Based on industry benchmarks, not Turivus measurements.
100 → 10/day
Actionable Alerts
4h → 15 min
MTTR
40% auto-resolved
Self-Healing
+50%
On-Call Productivity
Onboarding Agent
Guides new customers through setup and configuration.
Typical SME problem
New customers need 2 weeks for onboarding. High churn in the first month.
Agent architecture
Agent guides new customers through setup, answers FAQs, configures basics, diagnoses errors, escalates when needed.
Security behaviour
Onboarding data (API keys, integration config) is never sent to cloud APIs. Local processing only.
Expected impact range
Based on industry benchmarks, not Turivus measurements.
2 weeks → 2 days
Onboarding Time
15% → 5%
First-Week Churn
-60%
Support Tickets
1 week → 1 day
Time to First Value
Which blueprint sits closest to your situation? Let's run the numbers in 30 minutes.
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