Data & AI delivery.
Senior expertise.
Senior specialists and focused project delivery, with Azure, Databricks and AI at our core. Product management and Microsoft 365 expertise for the work around it.
Need a senior specialist? Discuss your requirementWorking on AWS, Google Cloud or Snowflake? Your requirements are welcome.
Trusted by ambitious teams
Most AI projects stall on the data, not the model.
Models are easy to get hold of now. What's hard is data that is clean, documented, governed and defined the same way everywhere, so that an analyst, a dashboard and an AI agent all give the same answer to the same question.
That work is unglamorous, and it's where we spend most of our time: building the platform, agreeing the definitions, putting a semantic layer on top, and only then connecting the AI.
- Curated, documented tables
- Metric definitions everyone shares
- Access and lineage you can audit
- Interfaces AI can use: Genie, APIs, MCP
How ready is your data for AI?
Ten questions, three minutes, an instant score across five areas.
Clear services. The right expertise.
- 01
Forward-deployed data & AI engineers
Senior engineers, architects and pods who work inside your team and stay through the outcome: lakehouse builds, migrations, SAP and CDC. Direct, or white-labelled for IT services firms.
- 02
AI-ready data consulting
Find out what your data needs before you build AI on it, then fix it: readiness assessments, semantic layers, governance and natural-language analytics.
- 03
Production AI agents
Agents and assistants grounded in your governed data, with evaluation, guardrails and monitoring from the first release.
- 04
Fractional Chief Data / AI Officer
Senior data and AI leadership a few days a month: strategy, platform decisions, governance and building the team.
- 05
Product management
Experienced product managers for discovery, prioritisation, roadmaps and product ownership, embedded in your team or your client engagement.
- 06
Microsoft 365 specialists
Specialist support matched to your Microsoft 365 applications, responsibilities and delivery needs. Relevant experience and availability confirmed against your brief.
Sectors we know, in the UAE and the UK
Strong foundations. Not a single-platform mindset.
Azure, Databricks and AI are our core strengths. For other platforms, we confirm the relevant experience and availability against your brief.
- Platforms
- Databricks
- Microsoft Fabric
- Snowflake
- Azure, AWS and GCP
- Data engineering
- Lakehouse design and build
- SAP ODP / BW extraction
- CDC and streaming
- dbt and analytics engineering
- Legacy ETL migration
- Semantics & governance
- Semantic layers and metric definitions
- Unity Catalog
- Lineage and access control
- GDPR, UAE PDPL and EU AI Act readiness
- AI on your data
- Databricks Genie
- Snowflake Cortex Analyst
- RAG and tool-using agents
- MCP servers over enterprise data
- Evaluation and guardrails
What this looks like in practice
Airline data your teams can question in plain English, from Slack
FareIntelligence works with large volumes of airline fare and pricing data. We provided data and AI engineers who built a governed semantic layer over that data and a Databricks Genie space on top, so people can ask questions in natural language from Slack.
- Questions answered in Slack each week
- ~350
- Typical time to an answer, down from 1 to 2 days
- < 30 sec
- Analyst time saved each week
- ~25 hrs
Questions answered in Slack each week
Typical time to an answer, down from 1 to 2 days
Analyst time saved each week
Client-reported, first eight weeks in production.
Read the case studyNeuraMach.AIA senior data modernisation squad in under three weeks
NeuraMach.AI won a data modernisation contract and needed a senior delivery squad, from solution architect to governance and delivery leads, before the programme kick-off date.
- To first shortlist per role
- < 48h
- Full senior squad onboarded
- < 3 weeks
- Roles filled from our own bench
- 100%
To first shortlist per role
Full senior squad onboarded
Roles filled from our own bench
“We won a data modernization contract and needed a full senior squad fast — solution architect through to governance and delivery leads. FracScale had the shortlist with us in days and the whole team in place inside three weeks. The programme landed successfully.”
Pay for outcomes where you can, capacity where you need it
Add a specialist to your team or engage FracScale for a defined workstream. We agree responsibilities, scope and commercial terms upfront.
Monthly · time and materials
Senior specialists
Data and AI engineers, product managers or Microsoft 365 specialists in your team. You direct the work; we support selection, onboarding and engagement oversight.
Milestone-based
Focused delivery team
A small team with a named delivery lead, agreed scope and acceptance criteria for a data or AI workstream. FracScale owns the agreed deliverables and handover.
Fixed fee · 2 to 3 weeks
AI-ready data assessment
We review your platform, data models, governance and target AI use cases, and hand you a prioritised plan with effort and cost.
Days per month
Fractional Chief Data / AI Officer
Senior leadership for data and AI strategy, platform decisions and governance, without a full-time executive hire.
From first call to people working, usually inside three weeks
- 01Day 0
Brief
A 30-minute call on the outcome you need, your stack and your timeline.
- 02Within 48 hours
Shortlist or scope
Named people for the roles, or a written scope and fixed price for a defined piece of work.
- 031 to 3 weeks
Start
You interview and decide. We handle contracting and onboarding so work starts in the first week.
A practitioner on every brief, not a sales desk

Jatin Asnani
Founder & Principal Consultant
Jatin has spent his career building and running enterprise data platforms: lakehouse architecture, SAP and CDC ingestion, governance, and the delivery leadership that keeps large programmes on schedule.
He started FracScale because the same problem kept coming up. Companies wanted to use AI, but their data wasn't ready for it, and the people who could fix that were either tied up in full-time roles or sitting behind a junior-heavy consultancy bench. FracScale puts those people directly on the work.
- Lakehouse architecture on Databricks and Azure
- SAP, CDC and large-scale ingestion
- Governance, semantic layers and Unity Catalog
- Natural-language analytics and production AI agents
Common questions
What does "forward-deployed" mean?
Our engineers work inside your team, in your tools and your stand-ups, and stay until the outcome is live and handed over. You get people who build and run the thing with you, not a report and a handover.
How is this different from staff augmentation?
For specialist capacity, you direct priorities and day-to-day work while FracScale supports selection, onboarding and engagement oversight. For a scoped project, FracScale owns the agreed deliverables and acceptance criteria. We make the responsibilities clear before work starts.
What does "AI-ready data" actually mean?
Data that is accurate, documented, governed and defined consistently, so a model or an agent can use it without guessing. In practice that means curated tables, a semantic layer with agreed metric definitions, clear ownership and proper access control. Our assessment tells you how far you are from that and what to fix first.
Do we need to be on Databricks?
No. Azure, Databricks and AI are our core strengths, but we welcome AWS, Google Cloud, Snowflake and Microsoft Fabric requirements. We confirm relevant specialist experience and availability against your brief rather than ask you to change platforms.
How do you price?
Assessments are a fixed fee. Delivery pods are priced by milestone. Specialists are billed monthly on time and materials, and fractional leadership by days per month. Rates depend on the skill and how scarce it is, and you get the number in writing before anything starts.
How quickly can people start?
Timing depends on the role, specialist availability and your onboarding and security checks. We confirm the shortlist or scoping timeline after reviewing your brief and agree a realistic start date before contracting.
How do you choose who to put forward?
Everyone we put forward has been assessed by practitioners on work they have actually delivered. You still interview and make the final decision.
What if someone isn't the right fit?
Raise the concern with your engagement contact. We review the issue and agree a resolution, including replacement options where appropriate, under the terms of your engagement.
Can you work under our brand?
Yes. IT services firms and consultancies use us as a white-label delivery partner. Our people work in your tooling, under your client contract and your delivery manager.
Who owns the IP and how is our data handled?
You own all work product and IP. Consultants sign NDAs and work under your security policies, and we can sign a DPA covering GDPR for UK and EU engagements.
Can we engage product managers or Microsoft 365 specialists?
Yes. These are available as specialist engagements alongside our data and AI work. We confirm the relevant product responsibilities or Microsoft 365 applications, practitioner experience and availability before proposing someone.
A project to deliver? A specialist you're missing?
Tell us your requirement, current environment and what you need next.

