Business software · Engineering teams · AI-ready delivery
Where Ideas Become Powerful Software Solutions
We build operational software for businesses running assets, field teams and compliance obligations — and staff the engineering teams that build it.
Flagship · AI data assistants
Ask your own systems a question,
and trust the answer
Your managers wait days for a report that has moved on by the time it arrives. We build assistants over the systems you already run — where the database decides who sees which rows, and the model is never allowed to produce a number.
- Not a prompt Row-level security means a generated query cannot return someone else's rows, even with no filter in it at all.
- Not the model's arithmetic Asked to total ten rows, a capable model returned 3,585, then 3,485, when the answer was 3,374. The server computes the totals.
- Measured, not assumed Between the cheapest usable model and the best one: two cents to forty-five cents per thousand questions.
About us
Sazinga builds and runs Sazinga Sarva, a platform of business applications for operators — the companies that run physical assets, field teams, production lines and regulated obligations. Alongside it we staff dedicated engineering teams in the same stacks those applications are built on. Each side keeps the other honest: a firm that has never run its own software in production is guessing about the parts that matter.
About SazingaSazinga Sarva
Seven of seven, in production today
Not a suite you have to buy into. Each application stands on its own — same team, same stack, same standards — so they join up when you need them to.
AI-Ready ODC
Two talent pools, one delivery centre
Most suppliers field application developers, or enterprise consultants. A real programme needs both, working to the same standard. You set the backlog, the priorities and the technical direction; we carry the recruitment, the retention, the leave cover and the replacement of anyone who is not right for the role — so you never carry a bench.
Product & platform engineering
Building and running software
- AI & ML engineers Features that use a model, not demos
- Frontend engineers Dense interfaces under real load
- Backend engineers The parts that must be provably right
- Mobile engineers Field apps that work without signal
- Cloud, DevOps & QA AWS and Azure as code; suites that can fail
Enterprise applications
Configuring, extending and integrating the estate
- SAP consultants Functional and technical, including ABAP and interfaces
- Oracle & ERP specialists Oracle, Dynamics 365 and the data behind them
- ServiceNow & ITSM Workflow, catalogue and platform development
- Integration engineers MuleSoft, Kafka, APIs, event spines, middleware
- BI & analytics developers Power BI, Tableau, Snowflake and Databricks
- Functional analysts Process, configuration and the specification behind it
AI is not a job title here. One group builds features that use models — retrieval, evaluation, guardrails, and knowing when a problem does not need a model at all. Everyone else is trained to use AI inside their own delivery: the developers, the SAP and Oracle consultants, the BI developers and the testers alike. The review bar does not move — a person signs off every change and their name is on the merge.
Our work
Explore what we have built and shipped
Specific problems need
specific software.
Tell us how the work runs today and we will tell you honestly whether one of the applications fits, or whether this is a build.
What clients say
I had a great professional experience with Sazinga's team. The team at Sazinga understands the scope of work well and acts with responsibility and competence to ensure a partnership is formed and builds into an enduring productive relationship.
Praveen PandeySagacity Software
Insights
All articles
245 bookings in the refund queue and no one could open it
A hire business asked for a sign-off step before refunds. The refund screen had never completed one. Our first diagnosis was wrong, and the owner corrected it.
A job assigned to a field user never appeared on the board
Creating a task failed on every submit. Once fixed, a task assigned to a field user reported success and then vanished from the supervisor's board.
A new field user with no boards assigned saw every board
Two new field staff were given no boards and could see all 101. A week later a user with 51 boards was shown 123 due out of 128. Two causes, one fix.