Ignitho

Enterprise AI in production - in weeks,
not another pilot

Pre-built AI accelerators that cut the time, cost, and risk of moving from proof-of-concept to production-grade ROI – deployed within your existing stack, governed from sprint one, and built on real enterprise delivery experience across regulated industries

ISG Noteworthy Provider

Advanced Analytics & AI

A Track record of Excellence

Since 2016

ISO 27001 Certified

Global Security Standards

Industry Partnerships

Databricks, Snowflake, Microsoft

IDA

Intelligent Data Accelerator

IQA

Intelligent Quality Accelerator

CQA

Conversational Agent Accelerator

CDP

Customer Data Platform Accelerator

Why Accelerators

Three-Pillar Philosophy
Time

From pilot to production in one sprint cycle

Most enterprises have AI projects that have been ‘almost ready for production’ for over a year. Our accelerators are pre-built, pre-tested, and pre-governed — which means your team spends time deploying value, not re-inventing infrastructure that already exists

Governed and compliant from day one

Every accelerator ships with enterprise security alignment, audit-ready data lineage, and human-in-the-loop controls. We have deployed these within the most strictly regulated BFSI, Pharma, and insurance environments in the world

Integration

Built on what you already own

No new licensing. No forced platform migrations. Every accelerator deploys within your existing cloud and data stack — AWS, Azure, Snowflake, Databricks, or whichever combination your organisation has already approved

87% of AI projects fail to reach production

ours don’t

The most expensive thing in enterprise AI is not the model. It’s the organizational debt that accumulates while a proof-of-concept sits on a shelf waiting for the engineering capacity, governance approval, or change management bandwidth to get it into production.  Ignitho Accelerators exist for one reason: to collapse the gap between ‘it works in the lab’ and ‘it runs in daily operations’ — by providing the pre-built components, governance frameworks, and deployment patterns that make production AI achievable in sprints rather than quarters

The 12-month POC shelf problem

AI pilots that impress in demos but never ship to production because the organisation lacks the MLOps infrastructure, governance framework, or engineering capacity to take them the last mile

⚠️

Data quality blocking every AI initiative

Over 90% of enterprises believe their data is too messy to start an AI project. Most abandon the initiative rather than solving the data problem first. Our IDA accelerator was built specifically to close this gap automatically

🔄

SDLC cycles too slow to keep up with business need

By the time a traditional development cycle tests, validates, and deploys an AI feature, the business requirement has changed. Slow quality assurance is the silent killer of AI value — IQA was built to end it

🔒

Adoption gaps that make AI invisible to the business

AI that requires users to learn a new interface, change their workflow, or trust a black box never gets adopted. The CQA accelerator solves this by integrating conversational AI directly into the tools your teams already use every day

87%

of AI projects fail to scale beyond pilot stage

99%

reduction in ETL effort through IDA self-healing pipeline agents

65%

reduction in SDLC time achieved through the Intelligent Quality Accelerator

18 months

average time for enterprise AI projects to reach production without accelerators

Four accelerators. One purpose: AI in production

Each accelerator addresses a specific failure mode in enterprise AI adoption — from data quality and pipeline debt to SDLC slowness and adoption gaps. All four are deployable within your existing stack, governed from sprint one, and proven in regulated enterprise environments

01

Intelligent Data Accelerator (IDA)

50–60% — Reduction in ETL overhead

An AI layer deployed between your datasets and your data pipelines that catches source changes proactively before they break downstream processes The result is self-healing data infrastructure that frees your engineering team from the maintenance loop

LLM Agents RAG Architecture Snowflake Databricks
02

Intelligent Quality Accelerator (IQA)

65% — Reduction in SDLC time

IQA rapidly validates your development lifecycle and eliminates the quality assurance stage that is too slow, too manual, enabling faster production deployment

AI Test Generation CI/CD GitHub Actions Azure DevOps
💬
03

Conversational Agent Accelerator (CQA)

100% — User adoption focus

CQA deploys NLP agents that meet users exactly where they work, integrating into existing tools like Slack and Teams to drive adoption

NLP Agents Slack LangChain OpenAI
📊
04

Customer Data Platform Accelerator (CDP)

ROI — From day one

Provides a defined path to ROI before a single sprint is planned, enabling customer intelligence without heavy platform investment

Customer 360 Snowflake dbt Power BI

From triage to production AI

in weeks, not quarters

Accelerators are not products you buy and configure yourself. They are deployments we run with you — scoped, customized, integrated, and governed within your specific enterprise environment by the same specialist POD teams that deliver our core services

Accelerator Fit Assessment Day 1 to 7

We run a rapid assessment of your current data estate, AI maturity, and highest-ROI use cases to identify which accelerator applies. No long discovery programme. One week. One prioritised deployment plan

Accelerator fit scorecard + sequenced deployment plan

Configuration & Integration Week 1 to 2

Each accelerator is configured for your specific environment — your cloud stack, security requirements, and approved platforms. We integrate with existing systems rather than adding new infrastructure.

Configured accelerator in your approved stack

Deployment & Validation Sprint 1 to 3

The accelerator deploys in live conditions alongside your team. Every sprint closes with measurable outcomes. Governance and explainability are built into every deployment from day one

Live accelerator deployment + outcome metrics

Stabilise, Optimise & Scale

Once in production, we optimise performance, document configuration, and enable your team to operate independently — or extend into new use cases as your AI programme matures

Production accelerator + runbooks + enablement

Our Specialist Partnerships

Partnering with industry leaders to deliver enterprise-grade solutions

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