Bring AI into real decisions – with the infrastructure to help your teams move faster without losing control.
AI is now defining the next generation of enterprise performance. The challenge isn’t access to models, it’s retaining control. Organisations don’t want teams experimenting across consumer AI, nor do they want a single model imposed across every workflow. They need auditable AI – enterprise-grade tools that improve time efficiency, operating on infrastructure that protects IP and preserves accountability.
Establish clear policy controls and evidence boundaries before any AI generation occurs.
Ensure every claim is traceable to source, outputs can be replayed and verified.
Standardise AI use within research workflows with approvals, audit trails, and data-aware updates.
Switch to the best models for a given workflow, while keeping governance layers consistent.
AI adoption spreads uncontrollably, through disconnected tools and experiments, creating inconsistent governance and decisions that are difficult to trace or defend.
Apex is our centralised licensing and governance layer that not only provides the control and guardrails needed to scale AI adoption across your organisation, but also preserves enterprise IP as durable institutional memory.
Set permitted sources, scope, and policy constraints before any generation
Re-evaluate decisions as data changes – with full audit continuity.
Set permitted sources, scope, and policy constraints before any generation
Re-evaluate decisions as data changes — with full audit continuity.
KiteEdge is used where decisions need to be defensible, licensed, or audit-ready.
ee where analysts agree, where they diverge, and what themes are actually emerging across the market.
Produce a fully referenced investment committee memo in minutes, not days — with every claim linked back to licensed research.
Understand what changed this quarter, how it compares to prior calls, and whether your thesis still holds.
Identify new risks or thesis-breaking signals across your holdings before they surface in performance.
Produce a credit paper with covenant appendix, enhanced by structured covenant extraction and variance flagging.
Deliver risk summaries with automated identification of covenant deviations.
Create comparative analyses supported by cross-transaction benchmarking.
Generate repricing risk briefs using market spread analysis with cited deal comparisons.
Produce screening memos using CIM extraction and sector benchmarking.
Deliver landscape briefs through consolidated broker synthesis.
Generate performance analyses using historical transaction comparisons.
Create valuation support briefs with comparable transaction and market evidence synthesis.
Produce compliance summaries through centralised regulatory mapping.
Deliver portfolio impact notes with linked source traceability.
Generate structured summaries with extracted and referenced clauses.
Create case risk assessment briefs using precedent synthesis with cited references.
Produce board-ready briefings with evidence-bounded executive summaries.
Deliver market positioning notes through external perception synthesis.
Create client-facing reports using cross-source research consolidation.
Generate investment prioritisation briefs with scenario comparison and cited evidence.
Contours is our first vertical implementation built on Apex infrastructure — designed for capital markets workflows where licensing, auditability, and investment-committee-ready outputs are non-negotiable.
Contours is our first vertical implementation built on Apex infrastructure — designed for capital markets workflows where licensing, auditability, and investment-committee-ready outputs are non-negotiable.
Contours is our first vertical implementation built on KiteEdge infrastructure — designed for capital markets workflows where licensing, auditability, and investment-committee-ready outputs are non-negotiable.
In decision-critical environments, the hard problem isn’t producing answers — it’s standing behind them.
KiteEdge provides the infrastructure that makes AI usable where accountability, provenance, and governance are non-negotiable.
Decision owners get clarity on what was decided and why
Serious decisions demand more than surface answers. They require structured and re-runable analysis across approved sources — with reasoning you can inspect.
Only approved sources, date ranges, and entitlements are included before any analysis begins. Access controls are enforced upstream, ensuring unauthorised or out-of-scope material is excluded by design, not filtered after the fact.
Every claim is traceable to specific passages within approved materials. Users can examine the underlying evidence directly, linking conclusions to verifiable source context rather than model interpretation alone.
Explicit policy boundaries prevent the system from speculating beyond available evidence. When information falls outside approved scope, the system refuses clearly and records why, avoiding false confidence.
Conclusions can be re-run against the same evidence base and constraints. Decision artefacts remain stable over time, enabling comparison, review, and audit as data evolves.
AI accelerates analysis, but decision authority remains with named owners. Approvals are explicit, recorded, and accountable.
Every output makes its boundaries visible: what sources were included, what timeframe applied, and what assumptions shaped the analysis. This ensures depth does not become drift and context is never implied.
Apex is our governance infrastructure for AI-assisted decisions. It sets the boundary on what evidence can be used, enforces access and provenance, and produces auditable decision records—so outputs are defensible and repeatable.
No. Assistants generate answers. Apex governs the workflow around AI: what data is allowed, how evidence is cited, when the system must refuse, and how decisions are recorded and monitored.
We don’t rely on model promises. We reduce hallucination risk by design: constrained evidence sets, entitlement-aware retrieval, mandatory citations, and refusal when evidence is insufficient. If a claim can’t be supported, the system should say so.
Governance means control of the rails: pre-retrieval permissions, source allowlists and date windows, evidence set visibility, audit logs, approval checkpoints, and reproducible re-runs. Humans still decide; KiteEdge governs the process and artefacts around the decision.
Every material claim is tied to its source documents, down to the relevant passage/section, so reviewers can verify quickly. Outputs are only as strong as the underlying evidence set.
The system refuses or flags uncertainty rather than guessing. This is a core safety feature—especially in regulated environments.
Access is enforced before retrieval and reasoning. Users only see outputs derived from sources they’re entitled to; non-entitled content never enters the reasoning context. Different users can receive different answers because they have different entitlements.
Licensed content, enterprise repositories, and user-provided documents—subject to your policies. You can include/exclude sources and set the “decision boundary” (scope) per workflow.
Contours is the first vertical application built on Apex middleware—focused on capital markets research workflows. Same governance infrastructure; different user experience and templates.
Typically into your environment (e.g., your Azure tenant) with your identity provider and logging. The goal is operational control: entitlements, auditability, and separation of customer data.
Apex supports re-runs against the same boundary and evidence context, so you can see what changed, why it changed, and which new documents caused the change.
Fast to start when you begin with licensed/known content and a defined workflow. The heaviest lift is usually policy/entitlement mapping and connecting enterprise repositories—KiteEdge is designed to make those constraints explicit rather than hidden.
