Challenge - Data Pipelines & Integrations

AI products fail on data before they fail on models.

Your pilot worked on a curated snapshot. Production data arrives schema-drifted, late, and inconsistently formatted. A third-party API changes without notice and an integration silently breaks. We build the pipelines, integrations, and data infrastructure that hold up once real traffic hits them — not just in the demo.

Where we help

The data engineering problems that block AI and product roadmaps.

These come from engagements where an AI feature, an analytics rebuild, or a product launch stalled because the data layer underneath it was never treated as a first-class engineering problem.

Your pilot worked. Production data looks nothing like it.

Curated snapshots powered the demo. Live data arrives schema-drifted, late, and inconsistently formatted — and the feature degrades within weeks while the data team gets blamed for assumptions the model team made.

Every new integration adds a schema nobody owns.

Five upstream sources, five schemas, no canonical model the team trusts — just a growing list of one-off fixes whenever a provider changes their API without notice.

A pipeline breaks and you find out from a Slack message, not a monitor.

Schema changes that pass validation but corrupt downstream aggregates, late-arriving events that look like missing data — invisible until someone notices the numbers are off.

Your AI feature is only as good as the pipeline feeding it

Feature stores, vector databases, and embedding pipelines built without observability or data quality checks make LLM and ML applications behave unpredictably in production, not just in notebooks.

Batch pipelines built for daily summaries can't keep up with what the business needs now

Query latency that makes real-time dashboards impractical, decisions made on data that's already hours old — the pipeline was never designed for the latency the business actually needs.

Building new data infrastructure from the ground up

A new product or AI feature built with the right pipeline architecture, integration boundaries, and data quality controls from day one is faster to extend than three years of patches on a pipeline that was never designed for production scale.

Proof of work

What comparable engagements delivered.

E-commerce - ActiDash
Billions of events processed, sub-minute dashboard refresh

ActiDash's clients were making business decisions on data 4–24 hours old. We rebuilt the ingestion and processing layer on a fault-tolerant Kafka streaming architecture — analytics dashboards now refresh on sub-minute cycles, delivered ahead of schedule with no scope reduction.

KafkaClickHouseAWS
Read the case
IoT - MirrorIOT
High-throughput sensor ingestion, zero cloud vendor lock-in

A lightweight, cloud-agnostic IoT platform supporting high-throughput sensor data ingestion, multi-tenant device management, and secure OTA firmware updates — deployable across any cloud or on-premises environment, eliminating vendor lock-in.

GogRPCCloud-agnostic
Read the case
Life Sciences
Forecasting model to production: 9 months to 90 days

A pharma supply chain forecasting model had been stuck in development for nine months. We rebuilt the pipeline with GxP-aligned validation, audit logging, and a kill-switch the QA team owns — deployed to production in 90 days with a validation package the regulatory team accepted without revision.

GoKafkaAzure
Read the case →
System types

What we build for data-dependent teams.

Most engagements involve more than one of these. A scoping call is the fastest way to identify what the real problem is and which category of work will fix it.

Learn about Product Pilot →
  • Data pipeline engineering — ingestion, transformation, delivery
  • AI data infrastructure — feature stores, vector databases, embedding pipelines
  • Third-party integrations — APIs, webhooks, CRM/ERP/payment systems
  • Analytics engineering — warehouse modelling, BI-layer design
  • Predictive and generative model development
  • ML model operations and governance
Client feedback

What clients say about working with us.

We brought Insoftex in after our second failed attempt at productionising the model. In six weeks they rebuilt the inference layer, instrumented it properly, and gave us an eval harness our own team could extend. They told us no twice during the engagement — both times they were right.
Jonathan Langley

Jonathan Langley

CTO · Azarc · UK

We're very happy with the outcome and already looking ahead to the next phase. What stood out most was Insoftex's strong sense of ownership, transparent and fast communication, and ability to think beyond the initial scope to continuously add value. From day one, they supported us in shaping the product vision, through to delivering a high-quality MVP. The result is a robust platform that enables customers to easily book advertising placements and effectively drive visibility and sales. A reliable and forward-thinking partner.
Fei Cheong

Fei Cheong

General Manager · US

We had a great experience working with the Insoftex team. They played an important role in delivering a modern application for power quality and energy generation analytics, owning both front-end development and automated QA. They built a flexible, user-centric dashboard with configurable widgets, making it easy to analyze data across devices, parameters, and time ranges. Insoftex combines strong technical expertise with a clear focus on quality and delivery. A reliable partner I'd confidently recommend.
Shimon Yannay

Shimon Yannay

Head of Software Development · Israel

Collaborating with Insoftex on our healthcare project proved to be transformative. Their team skillfully re-architected our platform based on comprehensive feedback, delivering exceptional results. They effectively addressed complex challenges while maintaining a strong emphasis on quality and precision. We look forward to continuing our partnership and highly recommend Insoftex to anyone seeking innovative, high-quality solutions.
Dmitry Shteyn

Dmitry Shteyn

CTO · VURVhealth · USA

Working with Insoftex on the social engagement platform, The Club of Names, was both productive and inspiring. They were involved far beyond development — they helped shape the product's concept and actively contributed ideas that strengthened its core functionality. Together, we built a platform that provides information about names, generates personalized articles, helps users select baby names, and includes a social feature — a chat for people with the same name to connect.
Jason Walker

Jason Walker

CEO · JWALKER Marketing · USA

I am happy to share my experience with Insoftex. They made for us a custom .NET application, and it is working very well! It fits perfectly with our needs, and the team did an excellent job integrating it within our local network. Their communication with Azure was seamless, and their professionalism made a big difference. We are pleased with the result and can highly recommend Insoftex for their dedication to quality work!
Thomas Marquardt

Thomas Marquardt

CEO · Marquardt Informatik · Germany

We are delighted to acknowledge that Insoftex skillfully programmed our frontend using React, meticulously bringing our design to life. Their adherence to our timelines and effective communication ensured a seamless and productive collaboration.
Ingmar Kruse

Ingmar Kruse

CEO · Sun Sniffer · Germany

This has been an amazing experience working with Insoftex, between the communication, the collaboration, and commitment to delivering results it has exceeded our hopes.
Madison Pratt

Madison Pratt

CTO · DLTChain · Canada

They don't do standard, off-the-shelf products. Rather, they keep their eyes on the market for the newest trends.
Chad Taylor

Chad Taylor

CEO · Hudson INC · USA

Insoftex's work quality surpassed my expectations. You are fantastic partners.
Emmie Reese

Emmie Reese

CEO · EpicFlow · USA

Insoftex team have been professional and enthusiastic. The team was always available (even during US-hours). Great job!
Andrew Wilson

Andrew Wilson

CTO · Stealth Startup · USA

Need the data layer your AI or product roadmap depends on?

Book a 30-minute technical call. Bring your pipeline problem, your integration backlog, or the data quality issue nobody has fixed yet.

Book a 30-min technical call

A senior engineer replies within one business day, often faster.

Press Esc to close