Transformation is a pipeline, not a pilot.
Enterprises do not need more demos. They need agents that run inside real workflows, under real controls, and get better every week. Our method turns AI ambition into a delivery pipeline that is measurable, governed and repeatable.
claims-triage-agent · v1.8 · eval gate
passed
claims-triage-agent · v1.8 · red-team suite
passed
kyc-refresh-agent · shadow mode on live cases
running
payment-exception-agent · refund over limit
awaiting approval
it-ops-agent · canary breached latency SLO
rolled back
Four gaps between a demo and production.
No evaluation
No proof, so no trust
Without a golden set, nobody can say whether the agent is right often enough. We define “good” before we build.
No integration
A chat window, not a workflow
Value only appears when the agent can read and act in your systems. We build typed tool contracts into your stack.
No ownership
Nobody's job to adopt it
Agents change roles, and roles need owners. Every agent has a named business owner and a scorecard.
No operations
Works on day one, drifts by month three
Models, data and processes change. AgentOps watches quality, cost and drift continuously.
Six phases. Each one ends in evidence.
The method runs once per engagement. The pipeline runs on every change. The autonomy ladder sets how far each agent may act. Every phase ends in a deliverable and a go or no-go decision.
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01
Assess
Find the work worth agentifying
- • Workflow mapping with the people who do the work
- • Task-level value and risk scoring
- • Data and system readiness across the nine foundations
- • A target autonomy level for each workflow
Deliverable: ranked agent backlog and business case
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02
Design
Blueprint before code
- • Agent roles and hand-offs in a multi-agent design
- • Tool contracts to your systems (APIs, MCP)
- • Guardrails, human checkpoints and escalation paths
- • A golden evaluation set built from real cases
Deliverable: agent blueprint, golden set and scorecard
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03
Build
Engineered, not prompted
- • Built in the AgentifAI pipeline
- • Specialist agents (architect, developer, QA, security) beside our engineers
- • Everything as code, every change evaluated
- • Deployed in your environment from the first day
Deliverable: production-grade agent behind all gates
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04
Prove
Shadow mode first
- • The agent works beside your team on live cases
- • Its decisions are compared with your experts'
- • Accuracy, time and cost measured against the scorecard
- • It goes live only when it clears the bar you set
Deliverable: evidence pack and go-live decision
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05
Operate
AgentOps, every day
- • A trace for every decision and tool call
- • Evaluation regression on every release
- • Drift, latency and cost monitoring with alerts
- • Human review queues and incident runbooks
Deliverable: service levels and a live scorecard
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06
Scale
From one agent to an agentic enterprise
- • A catalogue of reusable tools and agents
- • Platform patterns any team can build on
- • An AI governance board and centre of excellence
- • Training that turns users into agent supervisors
Deliverable: operating model and multi-year roadmap
The pipeline that builds your agents is made of agents.
We treat an agent like any critical software release, then go further. Behaviour lives in code: prompts, tools, policies, evaluations and infrastructure. Every change is a pull request that has to pass automated gates before a human approves it. Specialist agents write, test and attack each change. Our engineers decide.
Versioned
Every behaviour change is a reviewed commit.
Evaluated
Every release is tested against the golden set.
Reversible
Rollback to the last approved version is a tested, scripted step.
Own identity
Each agent has its own least-privilege identity, never a shared admin key.
- 01 · commit
Change as code
A prompt, tool, policy or eval change opens a pull request with its reason and its owner.
- 02 · build
Agentic build & review
Developer agents implement, QA agents write tests, reviewer agents challenge. Engineers own the merge.
- 03 · gate
Evaluation gate
Task success, grounding and tool-call accuracy against the golden set, with no regression on the last release.
- 04 · gate
Security & policy gate
Prompt-injection, jailbreak and data-leak tests, an automated red-team suite and dependency scanning, plus policy-as-code for what the agent may do, on which data, for whom. High-risk changes need sign-off.
- 05 · prove
Shadow & canary
Runs beside your team on live work, then on a slice of traffic, with automatic rollback if quality or latency slips.
- 06 · run
Run & learn
Traces, quality scores, drift and cost per outcome, with review queues and runbooks. Every failure and human correction becomes a new test case. The bar only goes up.
Autonomy is earned, one rung at a time.
Each agent starts low and moves up only with evaluation evidence and the business owner's written sign-off. Most enterprise value sits at levels 2 and 3. Level 4 is for well-bounded work with a proven record.
Assist
The agent researches and suggests. A person does the work.
e.g. policy Q&A, case summaries
Copilot
The agent prepares the work: drafts, case files, proposed actions. A person approves each one.
e.g. AML case preparation
Supervised
The agent acts within limits. People review samples and every exception.
e.g. alert triage, invoice matching
Autonomous within guardrails
The agent runs the workflow end to end, escalates what falls outside policy and logs everything.
e.g. password resets, ticket routing
Where we put the method to work.
Cybersecurity
An agentic SOC on a security data lake. Agents triage, investigate, hunt and gather evidence, and analysts make the calls.
Explore arrow_forwardVision intelligence
KYC and trade documents, drawings, diagrams and site images read like a specialist would, then turned into structured data you can check.
Explore arrow_forwardField operations
Dispatch, inspections, maintenance and reporting for crews and assets spread across a city, a network or a country.
Explore arrow_forwardAcross the enterprise
Customer operations
Complaint triage, case resolution and agent assist in Arabic and English.
Finance & back office
Invoice matching, reconciliations, payment exceptions and month-end close.
IT operations
Incident triage, change-risk review, routine requests and runbook automation.
Risk & compliance
KYC refresh, policy Q&A, control testing and audit evidence collection.
Procurement & HR
Vendor due diligence, contract review, onboarding and internal service desks.
Evidence for your risk committee, from the first sprint.
Regulated enterprises need to show what an AI system is, who owns it, how it was tested and what it did. We produce that evidence as a by-product of the pipeline, so governance does not slow delivery down.
We document each agent's purpose, data, tests and controls in a form your risk and compliance teams can map to the frameworks they use, such as ISO/IEC 42001 and the NIST AI Risk Management Framework. The compliance judgement stays with you and your auditors.
AI inventory
Every agent registered with its owner, purpose, data, model and risk tier.
Agent cards
Plain-language documentation of what each agent can and cannot do.
Searchable audit trail
Inputs, retrieved context, tool calls, outputs and approvals, logged in your environment and searchable.
Sovereign deployment
Your tenancy, an in-country region or on premises, with every data flow mapped before go-live.
Start with one workflow. Leave with a capability.
Discovery sprint
A value map, a readiness score across the nine foundations, a ranked backlog with its business case and the blueprint for the first agent.
Pilot to production
One agent built behind the full pipeline and proven in shadow mode against a scorecard agreed up front, ready for your go-live decision.
Managed AgentOps
We run and improve your agents and data platform against agreed service levels: monitoring, evaluations, cost and new releases.
Build, operate, transfer
We stand up your agent platform and centre of excellence, run it with your team, then hand over the platform, the documentation and the skills.
Agents need good data. See Data Intelligence.
Turn one workflow into proof.
A discovery sprint gives you a ranked backlog, a readiness score and a blueprint for your first production agent.
Book a discovery sprint