Ingest
Market and enterprise sources
Industry AI Transformation · Capital Markets
From market data to
decision ready evidence.
ShellKode connects market and enterprise data with research, monitoring and AI assisted workflows so analysts and control teams can reach judgment faster while keeping evidence, permissions and review authority visible.
How we create value
Industry context changes the engineering.
The operating friction
Research, client and control teams gather information from market feeds, internal systems, documents and alerts before analysis can begin. The bottleneck is often context assembly, not access to another model.
We use the friction to define the context, integration and controls the engineering has to solve not to generate a generic use case list.
How ShellKode intervenes
Engineer backward from the outcome.
01
Define the operating journey
Map the workflow, actors, systems, evidence, exceptions, approvals and business measure.
02
Build the context foundation
Connect the data, metadata, documents and enterprise systems the decision depends on.
03
Engineer intelligence into the workflow
Use models, agents and automation where they improve the decision or action-not because the technology exists.
04
Operate and measure
Keep human authority, evaluation, observability, governance and economics visible after go-live.
Structure
Entities, evidence and context
Analyze
Research or monitoring intelligence
Review
Analyst / control-owner authority
Act
Client, operations or filing workflow
Trace
Evidence, policy and economics
What we build
Four engineering motions.
One operating outcome.
01
Modernize market & enterprise data
Data pipelines, lakehouse / warehouse, entity context and controls.
So research and monitoring start with trusted, current evidence.
02
Engineer research & monitoring intelligence
Summarization, retrieval, anomaly / signal detection and AI assistance.
So teams spend less time gathering and more time interpreting.
03
Integrate authorized workflows
Research, client operations, surveillance and compliance processes.
So AI assistance connects to the workflow without bypassing controls.
04
Operate with traceability
Evaluation, permissions, model lifecycle, observability and resilience.
So outputs and decisions can be reconstructed when scrutiny is highest.
Proof
Proof from production.
60%
ShellKode's published 50Fin case study reports up to 60% faster CI/CD deployments and up to 30% savings across infrastructure and messaging after migration and modernization.
50Fin
Measures we design around
Agree the measure before the build.
Research & review cycle time
Alert quality & triage effort
Client operations productivity
Control & filing readiness
Questions buyers ask
Where can AI help in capital markets without replacing analyst judgment?
Research preparation, entity and document context, alert triage, surveillance evidence and client operations workflows can compress information assembly while preserving analyst or control owner review.
Can the architecture work with existing market data and surveillance systems?
Yes. ShellKode's approach is integration led: connect approved market, enterprise and workflow systems and introduce AI where it improves the decision process.
How do you evaluate capital markets AI?
Use workload specific evidence sets and measure accuracy, traceability, review effort, false positives / negatives where relevant, latency, cost and workflow impact.