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Intelligent Automation Services

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  • ENGINEER FOR SCALE

    Eliminate architectural bottlenecks. Modularize systems to support hyperautomation with built-in uptime, traceability, and change velocity.

  • STRUCTURE EXISTING DATA

    Establish a single source of truth. Clean fragmented pipelines, align schemas, and make enterprise data usable for ML inference and real-time orchestration.

  • ENABLE AI-ENHANCED AUTOMATION

    Move from task automation to decision automation. Embed models into production flows, integrate inference at runtime, and scale logic across the enterprise.

Why It Matters

Real automation begins where systems start thinking.

In 2025, automation no longer follows rules — it learns from outcomes. With artificial intelligence automation solutions, AI doesn’t just execute; it interprets, adjusts, and embeds logic into every layer of enterprise operations. This isn’t an upgrade. It’s a redesign of how systems behave under real conditions.

By 2037, the intelligent automation market is projected to surpass $84 billion, propelled by systems that not only run faster but also become more adaptive with every cycle. Across sectors such as fintech, logistics, manufacturing, and healthcare, the pressure to automate has shifted beyond mere efficiency. It now demands resilience, traceability, and decision velocity — all delivered in a production environment.

At Devox Software, we embed intelligence into the fabric of your operations, designed in from day one, never bolted on. We design machine learning models from the ground up, shaped by your real data, your constraints, and your velocity. And then we engineer the systems that carry them — resilient, traceable, built for inference in motion.

This is full-spectrum execution. Data pipelines that learn in real time. Architectures built for intelligent automation that adapt as fast as the market shifts. AI that doesn’t just observe outcomes, but drives them — with precision, with scale, with structural impact.

We move beyond tools, beyond templates.

We become the engine behind how your systems evolve.

What We Offer

Intelligent Automation Services We Provide

  • AI Readiness & Data Structuring

    We prepare your systems for intelligent automation by addressing structural complexity at both architectural and data levels. With the AI Solution Accelerator™, we run a focused transformation track that stabilizes execution paths, aligns semantics, and establishes the conditions necessary for scalable automation and production-grade machine learning.

    • Architecture Mapping & Breakdown. We catalog systems, services, and their interactions, highlighting tight coupling, integration drift, and points of failure that limit scalability and observability.
    • Data Lineage Analysis. We trace how data moves through the system, reconstruct process variants, and detect schema divergence, latency points, and logic fragmentation.
    • Dependency Review. We surface fragile seams, shared state, and undocumented integrations that prevent modular orchestration and runtime control.
    • Automation Readiness Evaluation. Each system component is assessed by feasibility, business impact, and ML compatibility, prioritizing areas that support stable, high-value automation.
    • Full-System Data Mapping. We build a complete picture of data propagation across domains, pipelines, and environments, pinpointing structural inconsistencies and semantic ambiguity.
    • Transformation Layer. We unify data definitions and encode transformations as versioned logic, enabling deterministic behavior and end-to-end traceability.
    • Governance & Runtime Control. We establish classification, policy enforcement, and observability rules to ensure quality, lineage, and regulatory alignment across the data lifecycle.

    Deliverable: a technically validated, ML-compatible foundation — the basis for an intelligent automation solution ready for inference integration, automation at scale, and continuous system adaptation under real-world load.

  • System Engineering Transformation

    Embed systems’ machine learning readiness.

    With our AI Solution Accelerator™, we redesign core system architectures to support intelligent automation under production constraints, including uptime, traceability, change velocity, and inference integration. This is the phase where brittle legacy codebases are transformed into modular, monitored systems that are fully compatible with machine learning (ML).

    The scope includes:

    • Reengineer for AI-native execution. With our AI Solution Accelerator™, we redesign systems at the architectural level to embed machine learning readiness — not as an overlay, but as infrastructure logic. Every layer is rebuilt to support inference, resilience, and continuous adaptation under production load.
    • Architectural Refactoring. We deconstruct monoliths into composable units where inference pipelines, learning loops, and logic abstraction can be independently evolved. Interfaces are rebuilt for runtime flexibility and AI-native orchestration.
    • Replatforming the Infrastructure. We migrate to environments optimized for real-time decision making — containerized, event-driven, and cloud-native. Each workload is optimized to support latency-sensitive machine learning tasks and elastic scaling of model execution.
    • Building the Monitoring Layer. Telemetry is redefined to track system health, along with AI behavior, thereby expanding visibility into how models operate in real-world conditions. We engineer observability into inference, surfacing drift, confidence anomalies, and version degradation directly from production flow.
    • DevOps Pipeline Automation. We extend CI/CD into the model lifecycle, incorporating version control, shadow testing, rollback strategies, and canary inference into your deployment pipeline. This enables the safe and auditable release of intelligence into operations.
    • ML-Ready Runtime Design. We prepare your system to operate with embedded AI from REST and streaming-based model execution to feature-store integration and feedback routing. On our intelligent automation platform, each model is treated as a runtime component, with full traceability and governance.

    Deliverable: a resilient, transparent, and modular system foundation — built to support automated decision logic and AI-driven workflows.

  • Process Mining

    See how your business runs — before you automate.

    We create digital twins of your workflows using intelligent process automation tools to surface bottlenecks, rework loops, and hidden inefficiencies. All powered by AI to guide automation where it makes the most impact.

    What we deliver:

    • Real-Time Process Intelligence. We extract event data from your ERP, CRM, and operational systems to visualize your actual end-to-end flows, including variants, detours, and delays.
    • AI-Powered Automation Readiness. Our models identify tasks that are ripe for automation — repetitive, error-prone, or costly — and score them based on ROI, complexity, and risk.
    • What-If Simulation & Optimization. Predict the impact of automation before it is rolled out. Run “what if” scenarios to evaluate efficiency gains, cost reductions, and systemic effects.
    • Continuous Monitoring with ML Insights. Deploy intelligent automation tools like anomaly detection, performance baselines, and real-time KPIs to validate outcomes and catch degradation early.
    • Compliance & Conformance Checking. We compare real-world execution to expected models and surface deviations, utilizing AI-supported diagnostics to identify and fix what’s broken.

    Outcome: A fact-based blueprint for automation that works — grounded in data, validated by AI, and tailored to your systems.

  • Intelligent Document Processing

    Handle messy formats.

    Enterprise workflows often rely on large volumes of unstructured and semi-structured documents: contracts, invoices, requests, and declarations. Manual processing introduces latency, inconsistency, and compliance risk, especially at scale.

    We build document automation pipelines that manage structural variability, enforce business rules, and integrate seamlessly with transactional systems.

    Scope includes:

    • Input Capture & Document Standardization. Ingest multi-format documents from email, portals, scanners, and APIs. Standardize encodings, orientations, and layouts to ensure consistent processing.
    • Contextual Parsing & Field Extraction. Use sequence modeling, layout analysis, and position-invariant parsing to extract entities, nested values, and business-critical fields with high accuracy.
    • Document Type Disambiguation. Apply classification models to distinguish structurally similar documents based on their semantic features. Route each document through a type-specific extraction and validation pipeline.
    • Cross-Validation & Logical Inference. Compare extracted data against internal systems, business logic, and historical patterns. Detect inconsistencies, enforce thresholds, and apply inferred corrections.
    • End-to-End Workflow Integration. Send verified data to core business systems, update state machines, trigger events, and generate audit logs. Embed the document process into the enterprise workflow without manual checkpoints.

    Outcome: a high-throughput document pipeline that handles ambiguity, enforces integrity, and eliminates human latency, without sacrificing accuracy or control.

  • Robotic Process Automation

    Make execution reliable.

    Repetitive, rule-based operations introduce latency and variability when executed manually, particularly in high-volume environments such as finance, human resources, customer service, and supply chain management.

    We design and deploy intelligent process automation services that mimic human interaction across interfaces and systems, while ensuring predictable behavior, full traceability, and no performance degradation over time.

    Engagement scope includes:

    • Process Deconstruction & Rule Capture. Analyze target workflows at UI, API, and data levels. Translate business rules, exception handling, and edge conditions into machine-executable logic.
    • UI Interaction Automation. Automate interaction with legacy systems, browsers, desktop software, and custom interfaces. Stabilize input fields, button hierarchies, and navigation logic under version drift.
    • Exception Management & Recovery Paths. Implement a structured approach for handling process failures, invalid data, missing fields, or downstream unavailability. Route to human-in-the-loop where required.
    • Scheduling, Orchestration & Load Control. Integrate with enterprise schedulers and queueing systems. Control concurrency, retry logic, and throughput caps to align with system capacity and business service-level agreements (SLAs).
    • End-to-End Monitoring & Audit Logging. Capture event traces, execution metrics, and error logs. Feed into observability platforms for compliance, performance analysis, and SLA validation.

    Outcome: a high-fidelity digital workforce that executes at speed, scales horizontally, and consistently enforces business rules.

  • Analytics & ML for Decision Support

    Predict operational outcomes.

    We design intelligent process automation solutions and ML systems to support tactical and strategic decisions in supply chain, finance, demand planning, and risk management. Models are engineered for production: trained on operational data, versioned, monitored, and connected to execution layers.

    Scope includes:

    • Objective Formulation. Turn business problems into prediction tasks: inventory needs, delivery ETA, credit default risk, fraud probability, revenue trajectory.
    • Data Conditioning. Align raw operational data to modeling standards: normalize formats, impute gaps, enforce consistency, and engineer temporal and categorical features.
    • Model Development. Use supervised learning, time series forecasting, anomaly detection, or classification, based on signal type and decision latency requirements.
    • Deployment Integration. Serve predictions via APIs, message queues, or direct system calls. Embed output into UIs, automated rules, or human-in-the-loop review.
    • Model Lifecycle Management. Watch how models perform, retrain when they drift, retrain on new distributions, and audit prediction behavior. Integrate metrics into the observability stack.

    Output: decision-grade ML embedded in core operations with measurable impact, traceable execution, and operational fit.

  • Conversational AI & Virtual Assistants

    Autonomous interaction. Embedded execution.

    Modern enterprise automation extends beyond forms and dashboards. It speaks, listens, interprets, and completes. We build conversational AI systems that absorb operational logic and deliver resolution—not just response—across voice, chat, and embedded UIs.

    These assistants process fragmented language, retrieve structured data, and perform transactional tasks. Each one is trained on your taxonomy, integrated into your architecture, and governed by traceable logic paths.

    Scope includes:

    • Semantic Parsing and Intent Modeling. NLP pipelines trained on domain-specific data, optimized for ambiguity handling, error correction, and task routing. Full support for synonyms, multilingual queries, and nested intents.
    • Contextual Persistence and Memory Graphs. Structured conversation memory that retains entities, goals, constraints, and historical turns across sessions. Enables cross-channel continuity and reduces cognitive friction.
    • Transactional Layer Integration. Assistant logic wired into APIs, CRMs, ERPs, and support platforms. Supports actions like booking, submitting, updating, escalating — executed within secure environments.
    • Monitoring, Traceability, and Governance. Comprehensive telemetry across usage, resolution paths, and exception flows. Each decision path is auditable. Includes human-in-the-loop controls, escalation handling, and compliance filters.
    • Deployment Across Interaction Surfaces. One logic core deployed across chat, voice, embedded widgets, and messaging apps. Uniform behavior, state synchronization, and identity continuity built in.

    Outcome: An autonomous interaction layer that reduces operational load, accelerates resolution, and enforces precision — with every session contributing to systemic learning.

  • AI + IoT for Predictive Monitoring

    Turn sensor data into action.

    In logistics and manufacturing environments, sensor data is ubiquitous but often underutilized. We integrate edge telemetry with scalable inference pipelines to detect degradation patterns, model failure risks, and enable proactive intervention. This is the phase of predictive reliability engineering.

    Key capabilities include:

    • Signal Acquisition & Synchronization. Acquire and synchronize telemetry data from distributed assets, including machines, fleet vehicles, environmental sensors, and control systems. Normalize sample rates and synchronize time series from multiple sources for unified analysis and interpretation.
    • Anomaly Profiling & Drift Detection. Train unsupervised and semi-supervised models to distinguish between acceptable fluctuations and signal degradation. Quantify temporal drift, persistence of outliers, and entropy changes in different signals.
    • Health Index Modeling. Construct composite health indicators per plant derived from multidimensional signal data. Track shifts against operational baselines and degradation thresholds to predict failure windows.
    • Event Prediction & Maintenance Optimization. Model the relationship between observed signal patterns and historical failure events. Optimize maintenance intervals, resource allocation, and alerting logic based on probabilistic risk assessment.
    • Deployment & Integration. Package models for edge or cloud deployment, with continuous monitoring and feedback loops. Integrate predictions into existing maintenance systems, dashboards, and alerting platforms to enhance operational efficiency.

    Deliverable: a production-grade predictive maintenance framework with embedded intelligence, adaptive learning, and direct operational impact.

Our Process

Our Approach

Through our intelligent automation consulting services, we work at the intersection of systems architecture and machine intelligence, reshaping how organizations move from fragmented operations to environments that support continuous learning, embedded inference, and automation that holds under pressure. Every phase is engineered with precision to go beyond automating what's already in place and get the system ready for what lies ahead.

01.

01. Set Clear Goals

We start by defining what automation and AI are expected to achieve within your domain, focusing on real-world operations rather than abstract ideas. Whether the goal is faster resolution time, risk-based decision routing, or process optimization through behavioral patterns, we translate business outcomes into system-level targets that can be engineered, measured, and sustained.

02.

02. Map and Prioritize

We map the real structure of your systems — service interactions, data propagation, transformation logic, and interface dependencies. Each point is assessed within our process automation services framework for automation feasibility, model compatibility, and inference stability. This produces a ranked set of targets: areas where AI can be embedded with high confidence and low disruption.

03.

03. Uncover Opportunities

Using structured diagnostics and system telemetry, we identify where automation breaks down and where learning would fail. This includes schema inconsistencies, temporal drift, opaque decision paths, and areas with unstable process logic. These are deeper than gaps in tooling — they're structural barriers to intelligence. We resolve them before models are introduced.

04.

04. Understand Your Operating Environment

We study how data behaves inside your system, tracking not only where it flows but how it transforms, accumulates, and degrades. We trace lineage across environments, detect divergence in process variants, and identify points where logic relies on implicit assumptions. This produces a model of your system built to support real-time inference and capable of much more than running automation scripts.

05.

05. Build a Roadmap That Delivers

We build a plan that moves intelligence closer to execution — step by step, system by system. This includes modular refactoring, stream alignment, input-output control points, and model hosting infrastructure. Every milestone is guided by the perspective of an intelligent automation consultant, accounting for model lifecycle, versioning, and integration boundaries.

  • 01. Set Clear Goals

  • 02. Map and Prioritize

  • 03. Uncover Opportunities

  • 04. Understand Your Operating Environment

  • 05. Build a Roadmap That Delivers

Value We Provide

Benefits

01

AI-Secure from First Principles

Risk is modeled from the inside out. Our delivery embeds access controls at the feature level, tracks lineage across the ML lifecycle, and enforces policy at the point of decision. Compliance frameworks, such as ISO 27001, GDPR, and NIST 800, are applied structurally, within the execution path, not alongside it. Risk is identified early. Controls are built in.

02

Intelligence Deployed in Production

We build systems where machine learning runs with clear intent — versioned, governed, and deeply integrated into enterprise logic. Our intelligent automation software ensures models operate as runtime components, integrated with your workflows, monitored through telemetry, and optimized with every cycle of real-world feedback.

03

Execution That Delivers Real Impact

We deliver under constraints that demand precision. Whether forecasting inventory shifts, mitigating financial exposure, or driving clinical prioritization, our AI systems remain stable under load, respond to changes, and produce outcomes that align with your business rhythm. Every release is structured for clarity, auditability, and adaptation.

Case Studies

Our Latest Works

View All Case Studies
Optimizing Migrations: Neural Networks for Column Classification and Anomaly Detection for a Tech Startup Optimizing Migrations: Neural Networks for Column Classification and Anomaly Detection for a Tech Startup

Optimizing Migrations: Neural Networks for Column Classification and Anomaly Detection for a Tech Startup

Advanced machine learning techniques streamline data table processing as part of an end-to-end product. Neural networks identify data types, detect anomalies, and classify columns for a smooth automated migration. Real-time. Accurate. Fast.

Additional Info

Core Tech:
  • Python
  • Keras
  • Pandas library
  • Scikit-learn
  • NLTK (Natural Language Toolkit)
Country:

USA USA

Configurable Document Automation Platform for Export Compliance Configurable Document Automation Platform for Export Compliance

Configurable Document Automation Platform for Export Compliance

A configurable AI-powered platform that automates export certificate generation across 34 countries, ensuring compliance with dynamic customs regulations.

Additional Info

Core Tech:
  • FastAPI
  • React 18
  • OCR (pytesseract, Google Gemini Pro)
  • PostgreSQL
  • AWS S3
  • Docker
  • GitHub Actions
  • AWS ECS Fargate
Country:

USA USA

Trading System for Confidential Market Execution Trading System for Confidential Market Execution
  • Fintech
  • ATS

Trading System for Confidential Market Execution

A fintech trading system enabling anonymous, low-impact transactions between institutional players.

Additional Info

Core Tech:
  • .NET Core
  • Kafka
  • Redis
  • React.js
  • WebSockets
  • OAuth 2.0
  • PostgreSQL
  • Selenium
Country:

USA USA

Testimonials

Testimonials

Sweden

The solutions they’re providing is helping our business run more smoothly. We’ve been able to make quick developments with them, meeting our product vision within the timeline we set up. Listen to them because they can give strong advice about how to build good products.

Carl-Fredrik Linné
Tech Lead at CURE Media
Darrin Lipscomb
United States

We are a software startup and using Devox allowed us to get an MVP to market faster and less cost than trying to build and fund an R&D team initially. Communication was excellent with Devox. This is a top notch firm.

Darrin Lipscomb
CEO, Founder at Ferretly
Daniel Bertuccio
Australia

Their level of understanding, detail, and work ethic was great. We had 2 designers, 2 developers, PM and QA specialist. I am extremely satisfied with the end deliverables. Devox Software was always on time during the process.

Daniel Bertuccio
Marketing Manager at Eurolinx
Australia

We get great satisfaction working with them. They help us produce a product we’re happy with as co-founders. The feedback we got from customers was really great, too. Customers get what we do and we feel like we’re really reaching our target market.

Trent Allan
CTO, Co-founder at Active Place
United Kingdom

I’m blown up with the level of professionalism that’s been shown, as well as the welcoming nature and the social aspects. Devox Software is really on the ball technically.

Andy Morrey
Managing Director at Magma Trading
Vadim Ivanenko
Switzerland

Great job! We met the deadlines and brought happiness to our customers. Communication was perfect. Quick response. No problems with anything during the project. Their experienced team and perfect communication offer the best mix of quality and rates.

Vadim Ivanenko
United States

The project continues to be a success. As an early-stage company, we're continuously iterating to find product success. Devox has been quick and effective at iterating alongside us. I'm happy with the team, their responsiveness, and their output.

Jason Leffakis
Founder, CEO at Function4
Sweden

We hired the Devox team for a complicated (unusual interaction) UX/UI assignment. The team managed the project well both for initial time estimates and also weekly follow-ups throughout delivery. Overall, efficient work with a nice professional team.

John Boman
Product Manager at Lexplore
Tomas Pataky
Canada

Their intuition about the product and their willingness to try new approaches and show them to our team as alternatives to our set course were impressive. The Devox team makes it incredibly easy to work with, and their ability to manage our team and set expectations was outstanding.

Tamas Pataky
Head of Product at Stromcore
Stan Sadokov
Estonia

Devox is a team of exepctional talent and responsible executives. All of the talent we outstaffed from the company were experts in their fields and delivered quality work. They also take full ownership to what they deliver to you. If you work with Devox you will get actual results and you can rest assured that the result will procude value.

Stan Sadokov
Product Lead at Multilogin
United Kingdom

The work that the team has done on our project has been nothing short of incredible – it has surpassed all expectations I had and really is something I could only have dreamt of finding. Team is hard working, dedicated, personable and passionate. I have worked with people literally all over the world both in business and as freelancer, and people from Devox Software are 1 in a million.

Mark Lamb
Technical Director at M3 Network Limited
FAQ

Frequently Asked Questions

  • What if we are not yet ready for machine learning?

    Then we begin where readiness takes form — inside the system.

    The AI Solution Accelerator™ works by clarifying how your architecture responds to input, how data behaves under load, and how logic is fragmented across workflows. Each signal reveals structural decisions: what holds, what drifts, what needs redefinition. We use those signals to build a foundation for learning.

    Data flows are stabilized. Schemas gain continuity. Execution paths are reshaped for inference without interruption. The environment starts supporting intelligence not just in theory, but in practice, and does so consistently over time.

    Machine learning is introduced only when every layer of the system has intelligent automation incorporated and is ready to support it. And at that point, the system no longer resists the model.

  • Can you work with IoT data?

    Yes, we treat it as a key data source. In logistics, manufacturing, and infrastructure, sensor data holds untapped insights. We collect telemetry data from machines, vehicles, and environments, synchronize it over time, denoise it statistically, and make it suitable for conclusions.

    Our pipelines process real-time data streams, detect early signs of deterioration, and predict disruptive events with actionable precision. We don’t just collect signals — we operationalize them.

    From the edge to the cloud, your IoT data becomes part of an intelligent system that anticipates and responds in a targeted manner.

  • Do you work with fintechs?

    Yes, intensively and consistently. We know what’s at stake: compliance, transaction integrity, latency, and trust. Fintech systems demand more than just performance — they require precision under pressure, standard verifiability, and resilience on a large scale.

    Our intelligent automation consulting work includes credit risk modeling, fraud detection, payment orchestration, and real-time decision engines. We’ve structured data pipelines under regulatory oversight, automated high-volume processes with deterministic logic, and embedded ML into workflows where milliseconds matter.

    There is no room for deviation in financial technology, and we are developing for this reality.

  • How do you deal with security and compliance?

    Security is built into every layer, from architecture to deployment. We assess your system boundaries, access controls, data sensitivity, and compliance. Our IT automation services ensure that controls follow the flow of risk, whether in finance, healthcare, logistics, or high-throughput SaaS environments.

    Compliance doesn’t just come after delivery. Frameworks such as ISO 27001, GDPR, or NIST are integrated into our workflows. Every policy has an enforcement point. Every decision is traceable. Risk remains contained, obligations are met, and you maintain operational confidence — all as a result of intentional design, never as a lucky break.

  • Can you integrate with our existing systems?

    Yes, of course. Integration is a key component of every solution we offer.

    We work within your current environment — ERP, CRM, legacy systems, internal APIs — and take our cue from how your data flows and where your decisions are made: no assumptions, just traceable logic and verified paths.

    We reconstruct undocumented behavior, stabilize interfaces, and ensure that every connection supports automation, scalability, and observability. Your systems remain intact — they are now aligned, responsive, and designed for coordinated execution.

  • How will we know that it works? What is the ROI?

    We define value before implementation starts.

    Every automation measure is directly linked to measurable results — lower costs, lower latency, higher throughput, or better control. We establish baseline metrics, estimate the operational delta, and validate progress in production.

    Our software automation services focus on actual KPIs: time to resolution, order accuracy, process efficiency, and risk exposure. The impact is evident in how the system behaves and how the business operates, far beyond what reports alone can capture. Real ROI comes from structural improvements that are sustainable, observable, and directly tied to how the work gets done.

  • Will this be scalable when we need it?

    Yes. Our intelligent automation solutions are designed to evolve in response to changing demand, not just tolerate it. That includes how inference behaves under load, how pipelines adapt to growing datasets, and how each component maintains its contract as complexity scales. We account for this early through modular design, asynchronous execution, and well-defined integration boundaries, so the architecture remains coherent even as volume, concurrency, and decision depth increase.

    With the AI Solution Accelerator™, we validate those scaling points as intentional steps in the transformation path, never as postponed problems. The result, unlike what most automation service providers offer, is a system that expands without hesitation, as it’s built on patterns that anticipate change, absorb pressure, and maintain their shape over time.

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