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AWS Premier Partner · Gen AI Delivery Lab

Agents aren't assistants anymore. They run the operation while your team sleeps.

AI used to be a tool that helped a person finish a task. Now it's a system that runs the task. The Gen AI Delivery Lab ships agents that take work off your queue, governed against the OWASP Agentic Top 10 from day one.

Agents don't sit next to your team. They take items off the queue, with audit trails their CISO can sign.
Talk to a Solution Architect → See the Lab →

Trusted by teams shipping on AWS

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The Core Insight

What investing in AI means depends on whether you've shipped one agent or fifty. We have a lane for each.

Most enterprises are still treating AI as a tool that helps people. The teams that actually ship treat AI as a system that operates: agents with bounded authority, governed orchestration, audit trails, and ROI tracked sprint by sprint. The gap between those two postures is widening every quarter.

95%
No Measurable ROI

Ninety-five percent of GenAI pilots delivered nothing the CFO could measure. Not because the models failed. Because the codebases and data they operated on weren't ready for them.

MIT, 2025
80%
Boundary Violations

Eight in ten organisations with deployed agents have already had boundary violations. Unauthorised access, unscoped mutations, cascading failures. The governance gap is documented and widening.

OWASP/Strata, 2026
6+
Workshops to Qualify

PUSH framework qualification before any code is written. Six workshops ordered by maturity. The wrong agent in production is more expensive than no agent at all.

Armakuni Lab
The Reframe

Adding AI to a broken system multiplies the breakage. We build the orchestration layer that makes agents safe to ship on AWS.

Armakuni's Gen AI Delivery Lab builds the engineering foundation first: PUSH-qualified bets, agentic orchestration with OWASP Agentic Top 10 controls, and Bedrock-native governance from day one.

The orchestration layer is yours. Bedrock AgentCore, Step Functions, IAM, CloudWatch, Audit Manager. Deployed under your IAM. Your engineers walk away with the repo, the runbooks, the commit history, and a working agent fleet.

The PUSH Framework

Five gates between a promising agent and a production incident. PUSH closes each one before code ships.

PUSH is how the Gen AI Delivery Lab qualifies bets, builds foundations, ships agents, and holds them accountable. Five gates. No agent reaches production without passing every one.

Qualify the bet
Map the boundary
Build on the Lab template
Govern in production
Track what matters
Gate 01 · Plan

Qualify the bet

Most agent ideas die at this gate, and they should. PUSH workshops separate the agents that will ship from the ones that will never recover their build cost. We qualify against ROI, governance fit, and team readiness before any code gets written.

Gate 02 · Understand

Map the boundary

Every agent operates inside a defined authority boundary. Permissions, data scopes, tool allow-lists, escalation paths. Mapped explicitly before the agent ever invokes a model. OWASP Agentic Top 10 controls baked in from day one.

Gate 03 · Ship

Build on the Lab template

AgentCore + OpenClaw orchestration, Bedrock Guardrails on every model call, Knowledge Bases configured for your data, MCP allow-listed for your tools. Five reference patterns. Pick the one that matches your shape.

Gate 04 · Hold

Govern in production

Every agent decision streamed to CloudWatch. Every tool call logged. Every model invocation traced. Audit-ready from the first request. The Bedrock Evaluator runs alongside production traffic; drift triggers a human review.

Gate 05 · DORA

Track what matters

Deploy frequency, lead time, change failure rate, recovery time. Plus agent-specific metrics: tool-call success, escalation rate, hallucination rate. Baselined day one, tracked every sprint, reported to your CFO.

What Runs Inside the Lab

Six AWS services do the heavy lifting. Your team learns the ones they didn't already know on the way in.

The orchestration layer is thin on purpose. It wires AWS primitives you are already paying for into a single governed flow. No new runtime. No new vendor.

Bedrock AgentCore
Bedrock AgentCore

Runs every agent invocation. Scoped per task, logged per call. Anthropic Claude, Titan, plus open-weight models.

Claude · Titan · Open-weight
AgentCore + OpenClaw
AgentCore + OpenClaw

Orchestrates multi-agent workflows. State machine on Step Functions. Every transition is auditable.

Step Functions · State machines
Bedrock Knowledge Bases
Bedrock Knowledge Bases

Your data, semantically retrievable. RAG patterns wired to your S3 buckets, your VPC, your IAM scope.

OpenSearch · RAG
MCP Tool Layer
MCP Tool Layer

Allow-listed tools per agent with parameter bounds and rate limits. No agent invokes a tool it wasn't granted.

OWASP ASI05 / Tool Misuse
Bedrock Guardrails
Bedrock Guardrails

PII filters, prompt-injection filters, denied-topic policies on every model call. Policy, not prayer.

OWASP ASI01 / ASI06
Bedrock Evaluator
Bedrock Evaluator

Production traffic evaluated alongside the live agent. Drift triggers human review. Hallucination rate tracked.

Continuous evaluation
What customers say
A Leading smart kitchen appliance brand
AI cook-time prediction shipped
Case study
Ralph Newhouse, ceo at Leading smart kitchen appliance brand, United States
Product Manager, CHEF iQ
Leading smart kitchen appliance brand, United States · Jonathan Shieh

We were impressed by Armakuni's level of engagement and the personal attention we received throughout the entire project. Their regular updates, demos, and willingness to brainstorm made it clear how invested they were in the work. It was enlightening to see their process and approach. Not only were they enthusiastic about the technical challenges of the problem, but they also constantly kept the end user experience in mind. Overall, it has been a pleasure working with Armakuni!

A Chicago based media archive and licensing company
Agentic AI in content pipeline
Case study
Badie Ali Executive, vp at A Chicago-area media archive and licensing company
AWS Account Manager
A Chicago-area media archive and licensing company · Brittany Bonar

I wanted to send a huge thank you for your tremendous partnership with A Chicago-area media archive and licensing company. We went from an intro call with their VP of Technology, having never spoken to the customer before, to MAP Lite funding approved and a Gen AI POC in motion, all in under two months. It was a truly bar-raising partnership. Can't wait to continue working together on A Chicago-area media archive and licensing company Group and many more customers to come\\!

Leading Canadian InsurTech SaaS platform
AI-powered legacy extraction
Case study
Amy Zupon, ceo at Leading insurance broker management system provider in Canada
GM and VP, Leading insurance broker management system provider in Canada
Leading insurance broker management system provider in Canada · Dimitrios Argitis

It was very easy to be engaged. I was very impressed because I felt like we were moving forward with very good discussions, very smart people, and a lot of empathy and care. Of course, I'm also putting forward people whose expectations I'm trying to manage and how they see this. So yeah, I would agree, wonderful team for sure.

One of the largest cinema networks in the U.S.
AI on the contact centre
Case study
Sean Gamble Presitent, ceo at One of the largest cinema networks in the U.S.
Senior Manager, Application Integration, One of the largest cinema networks in the U.S.
One of the largest cinema networks in the U.S. · Matt Suckel

Kudos to Armakuni for demonstrating the speed, precision, and partnership needed to turn a high-speed challenge into a success story.

The Payoff · Lab Engagement Timeline

Workshops qualify the bets.|The Gen AI Delivery Lab ships them.

Median outcomes across recent Lab engagements where teams ran the PUSH framework and the orchestration layer was deployed in their AWS account.

Week 0
PUSH workshop
Qualify the bet, scope the agent
Week 4
Reference pattern picked
Lab template instantiated in your account
Week 8
First agent in production
Bedrock Evaluator running alongside
Exit
DORA + agent metrics live
Tracked every sprint, reported every quarter
Workshops · Qualify the bet first

Six workshops, ordered by maturity.|The right agent in production starts with the right qualification.

AI Strategy & Governance
AI Strategy & Governance

Where to start, what to qualify, how to govern. Two-day workshop for execs and engineering leaders.

Walk away with
  • A portfolio view of which AI bets are ready to ship
  • Which need foundation work first
2 daysFree
2 DAYSFREEVIRTUAL OR ONSITE
Building Production AI
Building Production AI Agents

Hands-on workshop where your engineers build a Bedrock agent against your real data. End the day with a working agent that passes the OWASP Agentic Top 10 controls.

1 dayFree
1 DAYFREEHANDS-ON
OpenAI to Bedrock
OpenAI to Bedrock Migration

For teams already running OpenAI in production. Half-day workshop covering equivalence testing, prompt migration patterns, and feature-flagged cutover strategy.

Half dayFree
HALF DAYFREEVIRTUAL
RAG architecture
RAG Enterprise Architecture

Building Knowledge Bases that scale: chunking strategies, retrieval evaluation, per-tenant partitioning, citation patterns. Half-day workshop on real architectures.

Half dayFree
HALF DAYFREEARCHITECTURE DEEP-DIVE
Security for AI
Security for Product Teams in the AI Era

OWASP Agentic Top 10, prompt-injection patterns, tool-misuse vectors. Workshop for product engineers shipping AI features. End with a security review of your existing AI surface.

1 dayFree
1 DAYFREESECURITY REVIEW INCLUDED
PUSH framework
Push + Agentic AI Initiative Canvas

PUSH-driven prioritisation of your AI bets.

Walk away with
  • A qualified backlog: which bets ship now
  • Which need foundation work
  • Which to retire. Half-day for executives + engineering leads
Half dayFree
HALF DAYFREEEXECUTIVE WORKSHOP
Where Agents Land First

Agentic AI lands first where twenty humans work the same case today and every output is already auditable by the regulator.

BFSI
→
Core banking · Payments · Capital markets
BFSI

Thirty-year COBOL cores, monthly regulator cycles, and an AI roadmap the CTO already signed. The orchestration layer keeps every AI action audit-ready for the PRA, FCA, and SEC.

 Healthcare
→
Payers · Providers · Life sciences
Healthcare

PHI cannot leave the account. Guardrails and SCPs keep every Bedrock call inside HIPAA boundaries. Lab agents have shipped against claims, scheduling, and EHR-adjacent surfaces without a single cross-account spill.

 Retail
→
Omnichannel · Supply chain · Marketplaces
Retail

Peak-season refactors where a bad deploy costs a weekend of revenue. Canary gates inside Step Functions hold agents to the same release calendar your SREs already run.

 Manufacturing
→
MES · ERP adjacencies · OT-IT bridges
Manufacturing

Systems where a bad change takes a production line offline. Inspector and Config drift checks run before any Lab agent touches a service that talks to the shop floor.

 Telco
→
BSS · OSS · Network platform
Telco

Billing stacks that cannot go dark. The Lab targets adjacencies first, leaves the core untouched until the orchestration layer has proven itself, and keeps the whole carrier graph visible in CloudWatch the entire time.
Recent Results

How we helped real customers ship AI on AWS.|Three engagements. Specific outcomes.

Leading smart kitchen appliance brand, United States shipped AI cook-time prediction and recipe generation across smart kitchen appliances, with the model evaluator running alongside live traffic.

Read use case →

A Chicago-area media archive and licensing company automated metadata tagging and clip discovery on long-form archival video using a Gen AI PoC with audit-ready output.

Read use case →

Leading insurance broker management system provider in Canada used AI-powered PDF-to-JSON to extract a 25-year-old VB6 / Citrix platform during an AWS MAP Assess phase.

Read use case →

One of the largest cinema networks in the U.S. put AI voice agents and chat automation on Amazon Connect, wired to live data with full observability.

Read use case →

A regional agricultural cooperative in the U.S. Midwest deployed OWASP T1-T5 controls-as-code with AgentCore Memory isolation from day one.

Read use case →
More customer stories →
Continue exploring
Case studies
Case Studies

Real outcomes, real customers

Award-winning LMS provider for enterprises and mid-size organizations, the identity platform, One of the largest cinema networks in the U.S., SMS campaign automation platform for e-commerce and restaurant brands. Specific numbers. Named stakeholders.

All case studies →
Industries
Industries

Where this lands by sector

BFSI, healthcare, retail, manufacturing, telco. Constraints by industry. Response by orchestration.

All industries →
Insights
Insights

How we think about modernization

Engineering essays, AK Way deep-dives, AWS Premier Partner specializations.

Read insights →
AWS Premier Tier Services Partner

Named on the SOW. Specialized where it matters.

Active AWS competencies and service-delivery designations behind Gen AI and agentic work.

AWS
Premier
GenAI
Comp.
Migration
Comp.
DevOps
Comp.
Well-Arch.
Partner
EKS
Delivery
Lambda
Delivery
CFN
Delivery
+30 more
Migration and Modernization DevOps Consulting Competency Amazon EKS Delivery AWS Lambda Delivery AWS CloudFormation Delivery
Common questions

What CIOs ask before booking a Discovery Sprint.

How long is a typical Lab engagement?
A Gen AI Delivery Lab build runs eight to twelve weeks at fixed scope, with the Bedrock orchestration layer in place inside week three and the first governed agents in production by week six. Discovery and PUSH-qualified bet selection typically run two to three weeks before the build.
What does the team shape look like?
The Lab runs as a five-to-seven-person pod: solution architect, two Bedrock engineers, an evaluation specialist, a governance lead, and an AK Way practice owner for the Agentic Boundary Controls. Sized to the complexity of your AI surface, not bench utilization.
Does this only work on AWS?
The Lab targets AWS for orchestration and governance (Bedrock, AgentCore, Guardrails, Step Functions, IAM). PUSH and the workshops are cloud-agnostic. For teams currently on OpenAI or a non-AWS model, we run the OpenAI-to-Bedrock migration workshop first to qualify the move.
How do you handle agent safety and audit?
Every agent ships against the OWASP Agentic Top 10 controls. Bedrock Guardrails on every model call (PII filters, prompt-injection filters, denied-topic policies). MCP tool allow-listing with parameter bounds and rate limits. Every agent decision streams to CloudWatch; the Bedrock Evaluator runs alongside production traffic and triggers human review on drift.
What does success look like?
A qualified portfolio of AI bets, governed agents shipping into production, and the orchestration layer in your AWS account under your IAM. When the engagement ends your engineers have the repo, the runbooks, the CloudWatch dashboards, and the commit history. No vendor lock-in on the orchestration layer.
Discovery

One 30-minute call to qualify which AI bet to fund first.

Where you are with AI determines what we build first. Two-day PUSH workshop for execs. Half-day technical deep-dive for engineers. Either way, you walk away with a qualified path.

For your CTO/COO
Book a Discovery Sprint →
For your engineering lead
Contact us →

Your first conversation is with the solution architect who would run the engagement.