Services / 02 / Agents & enterprise knowledge
AI Agents, LLM Applications & RAG
Build grounded AI systems that can find evidence, reason across enterprise context, and take controlled actions.
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Discipline02 / 06
DeliveryEvidence → Production
ArchitectureModel · Product · Operations
01 / Engagement outcome02 · Agents & enterprise knowledge
Useful automation with citations, permissions, observability, and human authority designed in.
02 / Fit and scope
Start where the operational pressure is visible.
The first task is to separate the underlying system problem from the technology that may solve it. That keeps scope tied to evidence and operating value.
Operational signalsWhen this becomes relevant
- 01
Knowledge distributed across documents, databases, and inboxes
- 02
Teams repeating research, synthesis, and coordination work
- 03
Generic assistants that cannot cite or respect enterprise permissions
- 04
Agent prototypes that fail when tools, networks, or workflows change
Engineering ownershipWhat Aevum can own
- 01
Enterprise RAG and search
- 02
Tool-using AI agents
- 03
Document and OCR pipelines
- 04
Multi-agent workflows
- 05
Natural-language data interfaces
- 06
Evaluation, guardrails, and audit trails
03 / Delivery architecture
A controlled route to production.
Each stage should close a specific uncertainty and produce the evidence required for the next commitment.
Ground
Connect approved knowledge and preserve source, permission, and freshness boundaries.
Reason
Design prompts, retrieval, models, and tool plans against representative tasks.
Act
Integrate reversible tools with explicit authority, approval, and recovery behavior.
Evaluate
Measure evidence quality, task completion, correction effort, cost, and safe failure.
Control pointNo stage advances on momentum alone—evidence, decision, and ownership stay explicit.
04 / Technology
Selected around the operating constraint.
Tools are chosen for capability, deployment environment, team ownership, security, latency, reliability, and total operating cost—not vendor novelty.
05 / Related work
See the capability in context.
Delivered projects and production-minded blueprints showing how the engineering behaves inside a real domain.
View all case studies ↗
Delivered projectPhoto · HeadwayEnterprise
Local AI Meeting Assistant
A local-first assistant for transcription, action capture, and searchable meeting memory with enterprise retention controls.
View project ↗
Delivered projectPhoto · Luke ChesserEnergy
AI Chat Interface for Energy Data
An agentic query layer that translates business questions into governed filters, queries, maps, and cited analytical responses.
View project ↗06 / Connected disciplines
Most production systems cross more than one service boundary.
Make the first decision smaller
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