$1.8M→$620K
yearly run cost on a mid-market bank's integration estate — same scope, connected AI systems
12 wks
to replace 60 RPA bots and a full ESB estate with a reasoning connected AI systems
50–70%
typical run cost reduction in the first six months after mesh cut-over
0
silent data corruptions on records of truth — the mesh catches schema drift before it writes
The core problem
Sixty RPA bots and an $1.8M ESB. The real cost is what happens when one fails.
An RPA bot clicks through a fixed sequence of screens. An upstream upgrade moves a field. The bot fails, a ticket is raised, and the quarterly release cycle fixes it. In the meantime the flow sits broken or runs manually. Multiply that across sixty bots and add an ESB estate that breaks on schema changes it doesn't control, and the maintenance cost exceeds the value delivered.
A mid-market bank ran exactly that stack at $1.8M a year. Effektiv replaced the full estate with an connected AI systems in twelve weeks. New yearly run cost: $620K. APRA CPS 230 sign-off held. The bank's ops team now writes new flows in-house.
What changes
The same challenge. Two very different outcomes.
Without Effektiv
- RPA bots breaking on every UI change
- ESB jobs queued behind humans typing into screens
- Long-tail exceptions papered over by manual ops teams
- No replay harness — production traffic is the test set
- Run cost rising 8–12% year over year
- Vendor owns the integration map; lock-in is the model
With Effektiv
- Reasoning agents that recover from UI drift instead of breaking
- Agent mesh handles the long tail without the manual queue
- Live observability board your operations team reads daily
- Replay harness lets you test any production change against real traffic
- Run cost down 50–70% in the first six months
- Integration spec library, observable end-to-end, owned by your team
How we deliver
Diagnose. Design. Deliver.
Two weeks of listening before a line of code. The price is fixed at the end of Design — not at kick-off.
Phase 1 · 1–2 weeks
Diagnose
We read your bot logs, ESB queue map, and flow incident history. We map which flows touch money writes, which touch records of truth, and which are candidates for full automation. Silent failures — flows that complete without error but write corrupted data — are identified here.
Phase 2 · 1–2 weeks
Design
The mesh architecture, human-gate rules, and phase-out plan for the old stack. Any flow touching a financial record or a record of truth carries an explicit human approval gate. APRA CPS 230, ASIC RG 255, and equivalent frameworks mapped here. Price fixed at end of Design.
Phase 3 · 8–14 weeks
Deliver
The new mesh runs in parallel alongside the old stack until the evaluation period passes. The switch-over is clean and tested. Runbooks, eval rules, and mesh configuration are yours at exit — so the ops team can extend the mesh without calling us back.
Quality gates
What the quality checks measures.
Every output passes a multi-gate evaluation before it merges or ships. Outputs that fail do not proceed. The quality checks and all gate code are yours at exit.
- Integration latency under SLO per endpoint — budgets agreed in Design
- Data corruption rate at zero tolerance on records of truth
- Queue depth under sustained load, with back-pressure handling proven before cut-over
- Contract test pass rate across every external system the mesh talks to
- Message-loss tolerance under simulated upstream outage
Eval rig · sample run
Eval rig source code shipped to your repo at exit.
Sample engagement
A mid-market bank ran 60 RPA bots and an ESB estate at $1.8M a year. Bots fell over each quarter as upstream systems changed. Effektiv replaced the full estate with an connected AI systems over 12 weeks. New run cost: $620K. APRA CPS 230 sign-off held. The mesh now catches upstream schema changes before they corrupt the record of truth. The bank's ops team writes new flows in-house.
Read the full case →
Compliance posture
ISO 27001 in progress (Q3 2026) ISO 42001 aligned NIST AI RMF mapped IRAP path Q4 2026 Full governance posture →Other services
Other ways we work with you.
Service
Modernisation
AI archaeology decodes what the documentation missed. 11 weeks median.
Read more →Service
AI Adoption
With-you mode. Your team ships AI without us in 90 days.
Read more →Service
Software Build
Custom products and greenfield software, shipped in 8–14 weeks.
Read more →Service
Maintenance & SRE
AI in the alert path. 50–70% drop in human-paged incidents.
Read more →Service
Customer Experience
AI helpers that draft for human review. Never sends without a person in the loop.
Read more →Common questions
Frequently asked questions.
Outcome-priced against your current run cost
See what your integration estate costs to run with an connected AI systems.
Show us your current bot count, ESB estate, or ops team cost. We price the mesh on outcomes — your run cost reduction is the benchmark, not our hours.