A strategic value thesis for investors, incubators, and partners. Because in complex transformations, success is rarely won at the kickoff. It is won — or lost — in the proof.
For years, the same scene played out inside major financial institutions. A transformation programme would begin with ambition. Executive sponsorship. Large budgets. Top consulting firms. Confidence. Millions were invested to design the future. But one function — the one that would ultimately decide whether the change would work in the real world — was consistently treated as secondary.
As deadlines approached, pressure increased. Pass rates improved on paper. Defects were reclassified. Risks became "manageable." And the programme moved toward go-live carrying more uncertainty than leadership realised.
One recent case made the reality undeniable. A major institution had spent two years on a transformation. Soon after go-live, data sent externally did not match what was expected. Regulators stepped in. The Federal Reserve requested audit and remediation actions. Emergency workstreams were launched. Additional millions were approved.
The testing industry serves capital markets poorly. Not because the people are incompetent — but because the operating model is structurally broken. Three failure modes recur in every major CIB transformation.
A Murex upgrade. A Calypso migration. The programme runs for 18–24 months. Hundreds of millions invested. Go-live is approved. Then, within weeks, data discrepancies surface. Not a testing failure — a knowledge failure. The test team tested against specifications, not against the actual behaviour of capital markets products.
Every CIB transformation creates an enormous body of institutional knowledge. This knowledge lives in the heads of the delivery team. When the programme ends, it leaves with them. The next programme starts from zero. Not a retention failure — an architecture failure.
80%+ of production defects in major CIB programmes can be traced back to specifications — requirements that were misinterpreted, under-specified, or lost in translation. Defects that cost 10–100× more to fix in production. Not a quality failure — a traceability failure.
When the programme ends, the test artefacts become orphaned. There is no operating model for testing as a persistent, compounding asset.
Tricentis, Mabl, Testsigma, Functionize — strong products for generic SaaS testing. None understand what a CLS settlement exception looks like or what EMIR Refit requires.
No Tier 1 CIB runs a single-vendor stack. There is no vendor-neutral intelligence layer that works across the full estate.
The insight required to solve this problem has never been encoded into a product. Until now.
NeuroQA is not a test automation tool. It is a transformation assurance platform that combines proprietary CIB domain intelligence with multi-agent AI.
A Bloomberg-style two-layer taxonomy — universal CIB ontology at L1, client-specific instances at L2. Year 1 covers CLS + FX. Year 3 covers the full capital markets stack.
RAG-grounded generation: 590+ scenarios per domain, 90%+ accuracy, <5% hallucination. Every test traceable to a KG node and source document.
Vendor-agnostic API. Murex today. Calypso, Finastra, SBS, Temenos, Avaloq, ION, FIS next.
Unbroken audit trail from spec to result. DORA, Basel 3.1, EMIR Refit answered in seconds. Compliance becomes a product feature, not a project cost.
KG-powered delta analysis. When a product, rule, or regulation changes, the graph shows what breaks — before it breaks in production.
Regulatory and Compliance Intelligence. For DORA, Basel 3.1, EMIR Refit, and UMR, NeuroQA can demonstrate at any point what is covered, what passed, and where gaps remain.
Onboarding and Knowledge Transfer. A new consultant can ask "how does CLS settlement work for FX spot in this bank?" and receive a structured, sourced answer in seconds. Ramp-up time drops from months to days.
Impact Analysis for Change Management. When a rule, product, or system component changes, affected tests, data sets, and downstream dependencies are identified instantly.
Operational Risk Intelligence. Production defects and audit findings can be mapped back through the Knowledge Graph to identify systemic patterns.
Six specialist AI agents, each a deep domain expert in one capability. Coordinated by a LangGraph orchestrator — stateful, auditable, reproducible.
RAG grounding through a five-stage pipeline: Query → Retrieve (GraphRAG) → Rerank (Cohere) → Generate (GPT-4o / Claude) → Validate. Result: 90%+ accuracy, <5% hallucination. The Heart: Apache AGE on PostgreSQL — a property graph modelling CIB products, lifecycle events, regulatory rules, and client-specific instances.
DORA (January 2025), EMIR Refit, Basel 3.1, and UMR phase 6. Compliance-ready by default is no longer a premium — it is a mandate.
RAG + structured knowledge graphs crossed the production threshold in 2024–2025. LLMs grounded in domain-specific ontologies now achieve 90%+ accuracy — the level required for financial services.
No Tier 1 CIB runs a single-vendor stack. The market needs a vendor-neutral intelligence layer. Nobody has built one.
NeuroQA is not a startup idea. It is the productisation of twenty years of lived experience inside the most complex CIB transformation programmes in the industry — BNP Paribas, Société Générale, Natixis, UBS. Both sides of the table: writing the specifications and validating them.
| Segment | Value | Description |
|---|---|---|
| TAM | $24.25B | Global test automation market |
| SAM | $3.5B | CIB testing spend (Tier 1 + Tier 2 globally) |
| SOM | $120–250M | 3-year reachable with current architecture |
Bucket A — Horizontal AI platforms (Tricentis, Mabl, Functionize): zero CIB domain, category boundary not competitive threat. Bucket B — CIB specialists and SI accelerators (Murex-native, Luxoft, Capco, Synechron): domain-rich but locked to one vendor. Not reusable. Not compounding. This is where NeuroQA wins. Bucket C — Agentic adjacent (Devin, Cognizant Neuro): powerful platforms, no CIB knowledge.
Heart L1: CLS + FX deep. Document Intelligence. Test Generation L1–L5. First reference signed.
Calypso + 2nd client. AxiomSL. Full API execution. Reconciliation MVP. Co-case study.
Finastra, SBS, Temenos, Avaloq, ION, FIS. Self-healing. Connector SDK. 10+ clients.
NeuroQA is looking for the right partners to build the category. Four shapes of collaboration.
A technical co-builder who has delivered at CIB scale. Cloud, orchestration, KG, API layer.
Access to Tier 1 and Tier 2 CIBs. Joint offering. Reseller or white-label.
A named CIB willing to be the lighthouse. Murex MVP. Year 1 at cost.
Seed or strategic round. A strategic partner who sees the moat.