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governed intelligence plane
Research, models, and committee workflows resolve under shared policy and evaluation standards.
Meridian Capital
Intelligence 2025AI that investment committees can defend.
Meridian needed intelligence infrastructure where signals arrive with evaluation trails, policy gates, and human oversight — never a black-box island beside fiduciary duty.
40%
faster committee prep cycles
100%
model decisions attributable
0
ungoverned production models
Technology
- Python
- Laravel
- PostgreSQL
- Vector store
- Feature store
- OpenTelemetry
- Policy engine
- Kubernetes
Challenge
Insight without governance is liability.
Committee prep relied on fragmented research tools and ad-hoc models. Recommendations lacked attributable trails. Risk and compliance could not distinguish evaluated intelligence from speculative automation.
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Model outputs without evaluation history or policy context
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Committee materials assembled through manual archaeology each cycle
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No institutional plane connecting research signals to fiduciary decisions
Solution
Governed intelligence as institutional fabric.
We composed an intelligence layer where features, models, and committee workflows share evaluation, policy, and oversight. Every signal is attributable; every production path requires human judgment at defined thresholds.
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Feature and vector stores with lineage into committee-facing surfaces
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Policy engine gating model promotion and high-stakes recommendations
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Evaluation harnesses that travel with every production signal
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Human-in-the-loop checkpoints aligned to fiduciary decision points
Outcomes
What the investment institution gained.
40%
prep-cycle acceleration
Committees receive attributable signals faster without sacrificing fiduciary rigor.
100%
attributable decisions
Model influence is exportable evidence — not reconstructed narrative after the fact.
Gallery
Surfaces from the engagement.
Investment signals with evaluation context beside each recommendation.
Model performance and policy gates before promotion.
Lineage from feature to fiduciary decision.
Timeline
How the engagement unfolded.
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01
Fiduciary briefing
Investment, risk, and technology stakeholders defined decision points where human oversight is non-negotiable. -
02
Fabric foundations
Feature store, vector store, and policy engine composed with lineage and observability from inception. -
03
Committee surfaces
Governed recommendation workflows replaced fragmented prep archaeology for priority desks. -
04
Steady-state governance
Evaluation harnesses and promotion gates matured into institutional default for all production intelligence.
Results
Decision speed without diluting accountability.
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Faster, defensible prep
Investment committee preparation cycles compressed by 40% as research signals resolved into a governed plane of truth.
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Full attribution
Every model-influenced recommendation carries evaluation history, policy context, and operator identity — examinable, not theatrical.
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Zero ungoverned production paths
No model reaches production decisioning without evaluation gates and documented oversight thresholds.
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Risk and craft aligned
Compliance and portfolio teams share one observational fabric — intelligence beside the work, never a detached dashboard.
Client voice
“We do not want AI that impresses for a quarter. We need intelligence we can defend in committee — attributable, governed, and beside the decision, not above it.”
Have a challenge of similar gravity?
We brief investment, risk, and architecture stakeholders together — so evaluation of intelligence systems stays precise.