Services — Aevon.ai

01 — GPU & Inference

Reduce compute spend 40–60% without cutting capability.

Full-stack GPU fleet audit and right-sizing. Model quantisation (FP8/AWQ). Serving on vLLM or TensorRT-LLM with continuous batching and KV cache optimisation. Deployment on CoreWeave, Lambda Labs, or your existing cloud with 99.9% uptime SLA.

vLLM · TensorRT-LLM FP8 / AWQ quantisation CoreWeave · Lambda Labs Sub-100ms p95 SLA

Typical outcomes

10–30%

of current API cost per query

<100ms

p95 inference latency

inference_audit.py

import aevon.inference as inf

# Audit current stack

audit = inf.audit(stack="openai-gpt4o")

# Right-size to task

model = inf.select(

task="invoice-extraction",

accuracy_floor=0.97,

max_cost_per_1k=0.04

)

# → llama-3.1-8b-instruct-awq

# → cost reduction: 94%

Agent Mode — What gets automated

Infrastructure maintenance

Self-healing pipelines, auto-remediation, SLA monitoring

Model drift detection & retraining

Automated monitoring and scheduled retraining triggers

Compliance & audit trails

Continuous audit log, policy enforcement, regulatory reporting

High-volume workflow automation

Invoice processing, document extraction, customer service routing

02 — Agent Mode

Replace manual operations with autonomous AI maintenance.

We build autonomous agent workflows that handle infrastructure maintenance, compliance monitoring, and high-volume business processes. Drift detection, alert triage, auto-remediation — all without human intervention. Progressive autonomy: human-in-loop to fully autonomous as trust is established.

Autonomous maintenance Drift detection Salesforce · ServiceNow SOX · compliance

03 — Forward Deployed Engineers

Senior AI engineers embedded in your team.

Hands-on-keyboard implementation, not advisory. Our engineers work inside your infrastructure, your codebase, your delivery cycle. Knowledge transfer and team enablement are built into every engagement. When we leave, your team can own and extend everything we built.

Embedded delivery Knowledge transfer Structured exit India cost structure

40–60% below equivalent US specialist AI engineering firms. Senior engineers only — no GCC arbitrage, no juniors billed at senior rates.

How your team's time changes

Today60% maintenance / 40% product

Month 625% maintenance / 75% product

At exit85% product / 15% maintenance

AI agents handle maintenance. Your engineers build.

How every engagement starts

90-Day Discovery Sprint.

Fixed fee. Defined scope. Benchmarked output before you commit to the full build. We ingest your data and systems, identify the highest-ROI opportunities, and deliver a working prototype on your real infrastructure — not a demo.

Deliverable guarantee

Working prototype on your real data within 90 days — or we walk away. Fixed fee. No risk. No sunk cost.

Schedule the Discovery Sprint →

Week 1–2

System Audit

Map infrastructure, GPU fleet, data sources, current AI maturity.

Week 3–4

Data Ingestion

Connect to your systems. Ingest, cleanse, and catalogue datasets.

Week 5–8

Prototype Build

Working AI prototype on your real data. Production path, not a demo.

Week 9–12

Outcome Preview

Present benchmarked results. Define 18-month scope and metrics.

Production AI. Not strategy decks.

Reduce compute spend 40–60% without cutting capability.

Replace manual operations with autonomous AI maintenance.

Senior AI engineers embedded in your team.

90-Day Discovery Sprint.

Ready to see the numbers on your stack?