01
3
core AI delivery tracks
Production-Ready AI Delivery
AI Systems That Survive Real Operations
IMAI helps product and operations teams move AI from pilot decks into monitored production systems. We build computer vision, language AI, and agentic workflows that fit real data, real latency constraints, and real business KPIs.
Edge and cloud deploymentVision, voice, document, and agent workflowsHuman-in-the-loop governance
02
Edge
+Cloud
deployment targets
03
Vision
+Voice
multimodal pipelines
04
RAG
+Tools
agent orchestration
Why IMAI
Built for deployment, not demos
We structure AI work around operational constraints, measurable outcomes, and maintainable systems instead of one-off prototype wins.
Production-first architecture
We design for inference paths, observability, review workflows, and deployment environments from the start.
Shape the stack around inference, review paths, and deployment constraints before model choices lock in.
KPI-led delivery
Every engagement is framed around throughput, latency, accuracy, or automation targets that matter to the business.
Agree on throughput, latency, accuracy, or automation targets early so the delivery stays measurable.
Long-term maintainability
IMAI ships systems your team can monitor, extend, and operate after launch without hidden complexity.
Leave with a system your team can observe, tune, and extend after the first rollout.
Solutions
AI capabilities with a production path
Each track is designed around a workflow, validation milestone, and deployment architecture instead of isolated model experiments.
01
Computer Vision
Video and image systems for detection, recognition, inspection, and monitoring across facilities, roads, checkpoints, and industrial environments.
Realtime inference across edge cameras and centralized review pipelines.
Video AnalyticsDetection and TrackingOCR and LPRInspection Automation
View Computer Vision● LISTENING
TRANSCRIPT
02
NLP and Voice AI
Speech, document, and retrieval pipelines that convert conversations and unstructured content into searchable, automatable knowledge.
Built for multilingual transcripts, document intake, and knowledge workflows.
Speech-to-TextDocument AIEnterprise SearchText-to-Speech
View NLP Solutions03
Agentic AI
Assistants and workflow agents that retrieve knowledge, call tools, and complete multi-step tasks with control and auditability.
Designed for governed automation, approval loops, and operational handoffs.
RAG AssistantsTool UseWorkflow AutomationCopilot UX
View Agentic AILive Deployments
Systems we've shipped
Production deployments built and running for real operational workflows.
Computer Vision
Automated Toll Payment
License plate recognition and automated payment processing at toll checkpoints — edge inference, sub-second throughput.
Analytics
KPI Operator Monitor
Real-time KPI tracking dashboard for operations teams — live metrics, shift-level reporting, and performance alerts.
Agentic AI
AI Agent Workflow
Multi-step agentic automation that retrieves knowledge, calls tools, and completes tasks with audit logging.
Where We Fit
Operational teams we support
IMAI is strongest where automation needs traceability, performance targets, and clean integration into existing workflows.
Mobility and smart infrastructure
Video analytics, recognition, and alerting for roads, checkpoints, parking, access control, and smart city workflows.
Traffic monitoringLicense plate recognitionAccess control
Strongest where live camera events need to trigger alerts, review queues, or access decisions.
Document and back-office operations
Document AI, OCR, classification, and extraction for teams handling contracts, forms, statements, and internal records.
OCR pipelinesDocument extractionReview automation
Best fit when manual extraction, classification, or review is slowing high-volume teams.
Customer support and knowledge operations
Speech, search, and retrieval systems that help support teams find answers faster and automate repetitive service tasks.
Call transcriptionKnowledge searchSupport assistants
Ideal when answers are scattered across calls, documents, and internal knowledge bases.
Industrial and site monitoring
Detection, inspection, and anomaly-focused workflows for facilities, yards, and operational safety environments.
InspectionSafety monitoringEvent detection
Works best when safety, anomaly detection, or inspection speed directly affects operations.
Delivery Model
From workflow diagnosis to stable rollout
We move from business requirement to dependable deployment with a delivery process tuned for risk control, speed, and operational fit.
01
Problem framing
Map the workflow, data reality, deployment environment, and target KPI before model work starts.
Output: scoped workflow map, data assumptions, and a clear success metric.
02
Validation sprint
Pressure-test the approach on real samples and define what production readiness actually means.
Output: real-sample evidence, acceptance criteria, and a go or no-go signal.
03
Production build
Integrate models, orchestration, review loops, and infrastructure into a maintainable delivery stack.
Output: integrated stack, review loops, and deployment-ready architecture.
04
Rollout and iteration
Launch with monitoring, feedback, and a plan for drift, retraining, and operational support.
Output: monitoring plan, ownership model, and the next iteration backlog.
About IMAI
An AI engineering partner for operational teams
IMAI combines applied research, production engineering, and deployment discipline to help teams build AI systems they can trust in day-to-day operations.
Computer Vision • Language AI • Agentic Automation
Engineering depth
We work across modeling, inference optimization, data pipelines, and integration instead of stopping at a prototype.
Deployment discipline
We design with monitoring, fallback handling, latency budgets, and long-term maintainability in mind.
Practical collaboration
IMAI works with business and technical stakeholders to define scope clearly and ship usable systems faster.
FAQ
Questions teams ask before starting
The right engagement depends on the workflow, data quality, deployment target, and governance requirements.
Do you build pilots or full production systems?+
We can start with a scoped validation sprint, but the work is designed around a production path from the beginning.
Can IMAI deploy on edge devices, on-premise, or in the cloud?+
Yes. We design for the target environment, whether that is edge inference, on-premise infrastructure, private cloud, or a hybrid setup.
How do you validate that an AI workflow is ready for production?+
We define acceptance criteria around real samples, business KPIs, failure cases, and operational constraints before rollout.
Do you support multilingual AI workflows?+
Yes. We support multilingual document, speech, and retrieval workflows where the use case and data justify it.
Start with a scoped conversation
Planning an AI rollout or rescuing a stalled pilot?
Share the workflow, sample data, and deployment constraints. We will help you define the right scope, architecture, and validation plan.
Helpful inputs
A business process or operating problemSample video, audio, text, or documentsLatency, accuracy, security, or deployment constraints