Managed AI workflow systems

AI agents that ask before acting.

Ikhora turns meetings, documents, calls, and messages into reviewed, approved, measurable outputs. Agents do the work, pause at human review, then continue only after approval.

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Explore AI workflows
Human approval built in
Monitored after launch
Approval workflow
Static mobile view
Approved
Input
Context
Agent
Draft
Review
Gate
Client outcomes

Real pilots with measured workflow movement.

Every result below came from a human-gated workflow pilot: baseline first, approval path built in, then measured improvement after launch.

14 hrs saved/week
Meet-to-Spec
+42 bookings/month
AI Voice Receptionist
68% auto-resolution
AI Support Agent
MC14 hrs saved/weekMeet-to-Spec
DS+42 bookings/monthAI Voice Receptionist
LO68% auto-resolutionAI Support Agent
PN+47% demos bookedAI Inbound Sales Agent
JW80% less data entryDocument Intelligence Agent
AV3 days -> 4 hoursAI Recruiting Agent
MC14 hrs saved/weekMeet-to-Spec
DS+42 bookings/monthAI Voice Receptionist
LO68% auto-resolutionAI Support Agent
PN+47% demos bookedAI Inbound Sales Agent
JW80% less data entryDocument Intelligence Agent
AV3 days -> 4 hoursAI Recruiting Agent
14 hrs saved/week
Key outcome
“Cut post-meeting scoping from 8 hours to 45 minutes. The approval gate means zero bad outputs ever reach our clients.”
MC
Marcus Chen
VP of Delivery, Aether Digital Agency
Meet-to-SpecIT Agency
Want a workflow measured like this?

Start with one fixed-scope workflow, baseline the manual process, and get a before/after scorecard before expanding.

View results library
The operational gap

The work after the conversation is where execution breaks.

Client calls, support tickets, documents, and sales messages contain the decisions that move the business. Most teams still convert that context into tasks, proposals, records, and replies by hand.

Ikhora builds the system around the agent: inputs, retrieval, tools, approvals, monitoring, and ongoing optimization. The result is not a demo. It is a managed workflow your team can inspect, approve, and measure.

Before Ikhora

Manual workflow

Messy inputs
Meetings, PDFs, messages, emails, and call logs arrive in different formats.
Slow handoff
People copy decisions into tasks, proposals, records, and replies by hand.
Unreviewed action
Automation either stops at a draft or acts without enough business control.
With Ikhora

Gated flow

Reviewed
Agents extract, classify, draft, and flag uncertainty before anything moves.
Measured
Quality, cost, approval rate, and output completeness stay visible after launch.
Approved
Human review gates release downstream exports only after a real decision.
Flagship workflow

Start with Meet-to-Spec. Expand into monitored AI operations.

Convert client meetings into PRDs, feature lists, tasks, proposals, milestones, risks, and open questions. Every output is routed for human review before export.

View Meet-to-SpecDownload PDF Sample
Sample output set
Discovery call converted
Human review
PRD draft
User stories
Acceptance criteria
Milestone plan
Risk list
Jira export
Product ecosystem

AI agents for the work your team repeats every week.

Meet-to-Spec

From client meeting to project-ready specification.

Improves: 14 hrs saved per meeting cycle
View Meet-to-Spec
Document Intelligence Agent

Extract, validate, and act on document data automatically.

Improves: Data entry hours saved
View Document Intelligence Agent
AI Knowledge Base Assistant

Your internal knowledge base, made instantly queryable.

Improves: Answer accuracy rate
View AI Knowledge Base Assistant
AI Voice Receptionist

Never miss a call. Never lose a lead.

Improves: Calls answered rate
View AI Voice Receptionist
AI Customer Support Agent

Tier-1 support that actually resolves — not just responds.

Improves: Ticket resolution time
View AI Customer Support Agent
AI Inbound Sales Agent

Your best sales rep. Available 24/7. Never off-script.

Improves: Lead response time
View AI Inbound Sales Agent
Retail Checkout Automation

Cashier-less checkout, shelf inventory tracking, and exception alerts from camera feeds.

Improves: Retail computer vision
Scope custom workflow
Monitoring layer

Managed monitoring keeps every deployment observable after launch.

Quality checks, cost visibility, drift review, approval tracking, and monthly optimization are included in managed implementations so workflows stay reliable after launch.

View monitoring approach
Quality
Output checks, evaluation scores, regression tests
Cost
Token usage, cost per task, budget alerts
Approval
Review rates, escalation events, rejection reasons
Drift
Prompt regression, answer changes, anomaly detection
Delivery model

How Ikhora takes one workflow from audit to monitored deployment.

01
Audit one workflow
Map the inputs, decisions, approval gates, systems, and measurable baseline.
02
Build the agent
Configure prompts, retrieval, rules, integrations, and human review paths.
03
Launch with controls
Ship with approval queues, escalation rules, logs, and managed workflow monitoring.
04
Measure and expand
Track speed, quality, cost, approval rate, and ROI before adding more workflows.
Proof strategy

Measure the before and after. Do not ask buyers to trust magic.

Every serious deployment should define the baseline, review path, failure mode, measurement period, and optimization cadence before the agent is expanded.

Baseline before automation
Human approval for critical outputs
Source-cited knowledge retrieval
Drift, cost, and quality monitoring
Monthly optimization reports
Scoped expansion after measured value
Engagement paths

Start scoped. Earn trust. Expand deliberately.

AI Workflow Audit
1-2 weeks
Workflow map, ROI estimate, automation roadmap.
Productized Agent
2-6 weeks
One agent with approvals, integrations, and monitoring.
Managed AI Operations
Ongoing
Monthly optimization, reporting, cost control, and expansion.