Decisions you can trust the model on.
Data analytics, data engineering and enterprise AI - GenAI copilots, AI models, cloud AI pipelines and predictive analytics, engineered with guardrails, evals and the production discipline that turns pilots into outcomes.
Six capabilities. One AI & data platform.
From the data foundation to GenAI copilots in production - delivered as one accountable engagement with guardrails baked in.
Enterprise AI & GenAI
Production-ready AI copilots, agents and assistants built on your data with grounded retrieval, guardrails and human-in-the-loop review.
- RAG & vector search
- Agentic workflows
- Eval harnesses
Modern data platforms
Lakehouse and warehouse architectures with governed pipelines, semantic models and self-serve analytics for every team.
- Lakehouse on Snowflake / Databricks
- dbt & Airflow
- Semantic layer
Predictive analytics
Forecasting, segmentation, churn, propensity and pricing models embedded in operational workflows where decisions get made.
- Forecasting & demand
- Churn & propensity
- Pricing & uplift
ML platform & MLOps
Feature stores, model registries, deployment pipelines, drift monitoring and CI/CD for models from notebook to production.
- Feature store
- Model registry
- Drift & quality
Real-time data & streaming
Kafka, Flink and CDC-driven pipelines that move data in seconds for fraud, personalisation and operational intelligence.
- Kafka / Kinesis
- Flink / Spark Streaming
- CDC pipelines
AI governance & trust
Responsible AI guardrails, PII handling, model risk management and audit trails aligned with EU AI Act and ISO 42001.
- EU AI Act ready
- ISO 42001 aligned
- Red-team & evals
From use case to measurable outcome.
A disciplined four-step path that takes AI ideas from a whiteboard to production - with evals and guardrails at every gate.
Discover & frame
Identify high-value use cases, map data sources, define success metrics and shortlist models with a value-vs-effort matrix.
Data foundation
Stand up the lakehouse, ingestion, quality checks and a governed semantic layer so AI and analytics share one source of truth.
Build & evaluate
Develop models and AI features with offline evals, A/B tests and red-team reviews before promoting to production traffic.
Deploy & monitor
Ship with MLOps pipelines, drift monitoring, cost guardrails and feedback loops that keep models accurate over time.
What good AI delivery looks like.
The metrics our clients care about - accuracy, speed to insight and business impact, not just demos.
Best-in-class. Boring on purpose.
We pick the tools your team can hire for, operate safely and audit later - not the shiniest demo of the week.
- OpenAI
- Anthropic
- Azure OpenAI
- Bedrock
- Vertex AI
- Llama
- Snowflake
- Databricks
- BigQuery
- Postgres
- Iceberg
- Delta
- dbt
- Airflow
- Dagster
- Kafka
- Flink
- Spark
- MLflow
- SageMaker
- Vertex Pipelines
- Weights & Biases
- Evidently
- LangSmith
AI & data engagements that already shipped in your industry.
We bring industry-specific data models, regulatory playbooks and integration patterns from every vertical we operate in.
Financial services
Fraud detection, AML, credit risk, document AI and regulator-ready model governance.
Healthcare & life sciences
Clinical decision support, claims intelligence and PHI-aware GenAI with strict auditability.
Retail & commerce
Personalisation, demand forecasting, dynamic pricing and conversational commerce copilots.
Industrial & B2B SaaS
Predictive maintenance, anomaly detection and product copilots that lift activation and retention.
Senior delivery. Responsible AI.
No black boxes, no hand-offs, no hallucinated demos - just engineering that gets AI safely into production.
Responsible AI by default
Guardrails, eval harnesses and audit trails wired in from day one - aligned to EU AI Act and ISO 42001.
Data foundation first
We refuse to ship AI on broken data. Quality, lineage and a semantic layer come before any model launch.
Evals over vibes
Every model and prompt ships with an evaluation suite, regression gates and live drift monitoring.
Production engineering DNA
Senior MLOps and platform engineers ensure models scale, fail safely and stay within cost guardrails.
“The model is now part of the product, not a project.”
SyncTrix gave us a real data platform and a responsible AI program in one engagement. Our copilots ship with eval suites, our models ship with drift monitoring, and our auditors finally got the paper trail they kept asking for.
Questions we hear from data & AI leaders.
Have a different one? We are happy to walk you through approach, governance and references on a call.
Ready to ship AI that stays accurate in production?
Tell us your highest-value use case and the data you already have. We will come back with a 90-day plan, an architecture sketch and a senior pod to deliver it.
Tell us about your project.
Briefs, NDAs, architecture reviews, anything goes. A senior engineer responds within 24 hours.
- Email[email protected]
- Phone+91 99228 74956
- LocationsHyderabad · Pune · Bangalore
- 1 · A senior engineer reviews your brief within 24 hours.
- 2 · We schedule a 30-minute discovery call.
- 3 · You receive a written proposal in 48-72 hours.