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VIAHIND

Services

Engineering services for every layer of your digital systems

From a single internal tool to a complete data and AI platform, we design, build, integrate and operate software that solves a defined business problem. Choose a service below, or tell us the problem and we will recommend the right combination.

Discuss Your Project
01

Custom Software Development

The problem: Off-the-shelf tools rarely fit the way a business operates. Teams end up stitching spreadsheets, manual steps and disconnected products together — which slows work down and hides the data that matters.

The outcome: Software that fits your process, removes manual effort, and gives you full ownership of the code and the data.

Custom Software detailsDiscuss a project

What we build

  • Customer-facing web applications and portals
  • Internal operations tools and admin panels
  • Role-based business systems with approvals and audit trails
  • Modernisation of legacy applications onto maintainable stacks
  • Progressive web apps that work well on mobile

Typical deliverables

  • Requirements, user flows and a scoped delivery plan
  • UI/UX design for key screens
  • Production-ready source code in your repository
  • Automated tests for critical business logic
  • Deployment pipeline and environment setup
  • Technical documentation and handover

Relevant technologies

  • React
  • Next.js
  • Node.js
  • Python
  • PostgreSQL
  • MongoDB
  • TypeScript
02

AI and Machine Learning

The problem: Many AI initiatives stall at the demo stage: a model works in a notebook but never reaches the people who need it, or it cannot be trusted, monitored or maintained.

The outcome: AI features that are measurable, integrated into your existing tools, and designed to be monitored and improved after launch.

AI & Machine Learning detailsDiscuss a project

What we build

  • Forecasting, scoring and classification models
  • Document and text understanding pipelines
  • LLM-powered assistants grounded in your own data (RAG)
  • Recommendation and personalisation features
  • Model APIs that plug into existing applications

Typical deliverables

  • Problem framing, success metrics and data assessment
  • Baseline and iterated models with evaluation reports
  • Model serving API or batch pipeline
  • Monitoring for accuracy, drift and cost
  • Documentation of data, assumptions and limitations

Relevant technologies

  • Python
  • PyTorch
  • scikit-learn
  • LLM APIs
  • Vector databases
  • FastAPI
03

Computer Vision and Video Analytics

The problem: Businesses already record hours of camera footage, but almost none of it is used. Reviewing video manually is slow, and important events are noticed too late.

The outcome: Vision pipelines that extract the specific signals you care about — counts, events, occupancy, anomalies — and push them into dashboards and alerts.

Computer Vision detailsDiscuss a project

What we build

  • Object and person detection on live or recorded video
  • People counting, occupancy and footfall analytics
  • Zone, dwell-time and movement analysis
  • Visual inspection and quality checks from images
  • Event-triggered clips and evidence capture

Typical deliverables

  • Feasibility review of cameras, angles and lighting
  • Model selection, fine-tuning and evaluation on your footage
  • Edge or cloud inference pipeline
  • Event, metrics and evidence storage
  • Dashboards and alert integrations
  • Privacy and data-retention configuration

Relevant technologies

  • OpenCV
  • PyTorch
  • YOLO-family detectors
  • RTSP/ONVIF
  • GStreamer
  • Docker
04

Data Engineering and Analytics

The problem: Data is spread across applications, spreadsheets and third-party tools. Reports disagree, numbers are reconciled by hand, and nobody is sure which figure is right.

The outcome: A single, documented data foundation with automated pipelines your teams — and your AI initiatives — can rely on.

Data Engineering detailsDiscuss a project

What we build

  • Ingestion from databases, SaaS tools, APIs and files
  • Batch and near-real-time transformation pipelines
  • Data warehouses and analytics-ready data models
  • Data quality checks and alerting
  • Event and telemetry pipelines for products and devices

Typical deliverables

  • Source inventory and target data model
  • Orchestrated, version-controlled pipelines
  • Warehouse or lakehouse setup
  • Data quality tests and lineage documentation
  • Access controls and cost monitoring

Relevant technologies

  • Python
  • SQL
  • dbt
  • Airflow
  • PostgreSQL
  • BigQuery
  • Kafka
05

Business Intelligence Dashboards

The problem: Leaders wait days for reports that are out of date when they arrive, and existing dashboards are cluttered with metrics nobody acts on.

The outcome: A focused set of KPIs, delivered automatically, with the ability to drill into the detail behind every number.

BI Dashboards detailsDiscuss a project

What we build

  • Executive and operational KPI dashboards
  • Self-service analytics for business teams
  • Embedded analytics inside your own product
  • Scheduled and alert-based reporting
  • Custom visualisation for domain-specific data

Typical deliverables

  • KPI definitions agreed with stakeholders
  • Semantic layer and metric definitions
  • Dashboard design and build
  • Row-level security and access setup
  • User onboarding and documentation

Relevant technologies

  • Power BI
  • Metabase
  • Apache Superset
  • Looker Studio
  • React charting
  • SQL
06

Workflow Automation and Integrations

The problem: Teams spend hours copying data between systems, chasing approvals and sending routine updates. Errors creep in and processes depend on individual people remembering steps.

The outcome: Processes that run consistently, with fewer manual touchpoints, clear audit trails and less dependence on individual effort.

Workflow Automation detailsDiscuss a project

What we build

  • Approval and request workflows
  • Automated data entry and synchronisation between systems
  • Notification and escalation rules (email, chat, SMS, WhatsApp)
  • Document generation and processing
  • Scheduled jobs and back-office automation

Typical deliverables

  • Process mapping of the current and target workflow
  • Integration design and error-handling strategy
  • Automated workflows with logging and retries
  • Operational runbook and monitoring

Relevant technologies

  • Node.js
  • Python
  • REST & webhooks
  • n8n
  • Message queues
  • Serverless functions
07

SaaS Product Development

The problem: Founders need to validate an idea quickly without building a prototype that has to be thrown away. Product teams need a platform that can scale without a rewrite.

The outcome: A product that launches quickly on a sound architecture, ready for real customers, billing and growth.

SaaS Products detailsDiscuss a project

What we build

  • MVPs scoped around the core value proposition
  • Multi-tenant architecture with tenant isolation
  • Authentication, roles and organisation management
  • Subscription billing and usage metering
  • Admin consoles, analytics and audit logs

Typical deliverables

  • Product scoping and release roadmap
  • UX design for core user journeys
  • Production application and infrastructure
  • CI/CD, observability and error tracking
  • Post-launch iteration support

Relevant technologies

  • Next.js
  • Node.js
  • PostgreSQL
  • Stripe / Razorpay
  • Redis
  • Docker
08

Cloud Infrastructure and DevOps

The problem: Manual deployments, unclear environments and missing monitoring make every release stressful. Outages are discovered by customers, and cloud bills grow without explanation.

The outcome: Reproducible environments, automated deployments, monitoring that catches problems early, and infrastructure costs you can explain.

Cloud & DevOps detailsDiscuss a project

What we build

  • Cloud architecture and migration plans
  • Infrastructure as code for repeatable environments
  • CI/CD pipelines with automated testing
  • Containerised and serverless deployments
  • Monitoring, logging, alerting and backups

Typical deliverables

  • Architecture diagram and environment strategy
  • Infrastructure-as-code repository
  • Deployment pipelines for each environment
  • Dashboards, alerts and incident runbooks
  • Security baseline and cost review

Relevant technologies

  • AWS
  • Azure
  • Google Cloud
  • Vercel
  • Docker
  • Kubernetes
  • Terraform
  • GitHub Actions
09

API and Backend Engineering

The problem: Systems that cannot talk to each other create duplicate data and fragile manual workarounds. Poorly designed APIs become difficult to change and hard to secure.

The outcome: A clean integration layer with stable contracts, proper authentication and the performance to support growth.

APIs & Backend detailsDiscuss a project

What we build

  • REST and GraphQL APIs
  • Third-party and partner integrations
  • Event-driven and queue-based services
  • Authentication, authorisation and API key management
  • Performance optimisation of existing backends

Typical deliverables

  • API design and OpenAPI specification
  • Implemented services with automated tests
  • Rate limiting, logging and error handling
  • Developer documentation
  • Load testing and performance report

Relevant technologies

  • Node.js
  • Python
  • Go
  • PostgreSQL
  • Redis
  • OpenAPI
  • RabbitMQ

How engagements work

The same delivery process behind every service

Whether we are building a dashboard or a complete platform, work moves through clear stages with defined deliverables — so scope, progress and quality are visible throughout.

  1. 01 / 06

    Discover

    Understand the business problem, users, constraints and what success looks like.

    • Problem statement
    • Requirements
    • Success metrics

    Investment is aimed at the right problem from day one.

  2. 02 / 06

    Architect

    Design the system, data flows and integrations, and choose a technology stack that fits.

    • Architecture diagram
    • Technical plan
    • Delivery roadmap

    Risks are surfaced early, before they become expensive.

  3. 03 / 06

    Build

    Develop in short, reviewable iterations with automated tests and regular demos.

    • Working increments
    • Tested code
    • Progress demos

    You see progress continuously and can change direction.

  4. 04 / 06

    Integrate

    Connect the solution to your existing applications, data sources and devices.

    • APIs and connectors
    • Data migration
    • Integration tests

    The new system works with your business, not beside it.

  5. 05 / 06

    Deploy

    Release to production through automated pipelines with security and rollback in place.

    • CI/CD pipeline
    • Production environment
    • Runbooks

    Launches are predictable and low-risk.

  6. 06 / 06

    Monitor & Improve

    Track performance, reliability and usage, then iterate based on real-world data.

    • Monitoring and alerts
    • Usage insights
    • Improvement backlog

    The system keeps delivering value after launch.

Not sure where your project fits? Describe the problem and we will recommend an approach

Ready to build?

Have a business problem technology should solve?

Tell us what you are trying to achieve. We will review it and come back with practical next steps — a scoped project, a feasibility check, or an honest recommendation.

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