The discipline that delivered $2M+ procurement savings, 20% cost reductions and unified decision platforms for global enterprises — now productised for governments, PSUs, states and development partners.
Who we are
Reports show what happened. Dashboards show what is changing. Decision intelligence tells teams what to do next — and AI makes those decisions faster and more scalable. That is the shift we deliver in public systems.
KPI architecture, executive cockpits and review cadences that improve decision quality across departments.
Procurement, scheme, cost and productivity opportunities surfaced with practical, auditable analytics.
AI embedded in daily official workflows where it demonstrably saves time and improves decisions.
Architecture, governance and adoption models that make institutions AI-ready — no hype.
Standards, APIs and consent models that let departments exchange data lawfully and usefully.
Hands-on training that leaves government and CSO teams able to run, audit and extend what we build.
Why government, why now
India's digital public infrastructure now reaches beyond identity and payments into data exchange — creating the rails analytics and AI can finally run on.
National AI missions and state AI policies are actively pushing adoption — with governance, evaluation and capacity gaps that need exactly our skill set.
GeM and state e-procurement platforms have created years of structured spend data — recorded, but largely unmined. The enterprise playbook applies directly.
UNDP, the World Bank and GIZ are tendering AI capacity building and digital platform work right now — live opportunities we are positioned to answer.
The window: reference implementations built in the next two to three years become the templates other ministries, PSUs and states copy. Early, credible movers define the category.
The challenge
DPRs and bids are reviewed page-by-page; quality varies by reviewer and queues stretch to months.
Departments run siloed systems with no shared standards; citizen data is re-collected at every door.
Single bids, repeat winners and collusion patterns hide inside e-procurement data that no one mines.
AI tools enter operations through vendors with no registry, risk classification or human oversight.
Portals exist, but drop-offs, exclusion and citizen satisfaction go largely unmeasured.
A framework that sequences the fix — Digitise, Connect, Analyse, Govern, Deliver — with a productised offering behind every layer.
Consistent with challenge themes in the World Bank GovTech Maturity Index (GTMI) and UNDP digital governance assessments.
Our framework
One organising framework for every engagement. Each layer has a productised offering behind it, scoped to stand alone or sequence into the next.
Flagship AI solutions
Human-in-the-loop by design: AI drafts, accountable officials decide — with every flag evidence-linked for audit and appeal.
AI-assisted appraisal of Detailed Project Reports — completeness, compliance, cost benchmarking and risk, evaluated in days instead of months, with a full audit trail.
1. Ingest — OCR and structure extraction across DPR volumes → 2. Extract — costs, timelines, clauses, clearances → 3. Evaluate — rules, benchmarks and AI review across five lenses → 4. Score & flag — traffic-light report, each flag linked to its source page → 5. Decide — reviewer copilot; officials approve with full audit trail.
For ministries, state planning and finance departments, and funding agencies appraising infrastructure and scheme DPRs. Impact ranges indicative from comparable document-intelligence deployments; validated during pilot.
A bid-evaluation copilot plus red-flag analytics across the procurement lifecycle — responsiveness checks, evaluation matrices and 20+ integrity indicators.
In: e-procurement records, bid documents, supplier and ownership registries, contracts and payments, geospatial and project data. Engine: evaluation copilot, a 20+ indicator risk library, and risk scoring that routes high-risk cases with evidence files. Out: a committee evaluation workbench, oversight risk dashboards and evidence-linked case files.
Aligned with World Bank ProACT / GRAS-style procurement analytics. Built on the same methods that delivered $2M+ savings and 100% spend visibility in our enterprise procurement engagements. Impact ranges indicative; validated during pilot.
The six offerings
Every offering maps to a layer of the Decision Intelligence Stack and is priced and phased to be sanctionable.
Credentials
We are not entering government with theory — we are transferring a working method to a domain that needs it most.
Consolidated fragmented ERP spend into a category × supplier × time spend cube; built KPI governance and savings-realisation tracking that turned procurement from cost centre to value driver.
Normalised SKUs across facilities, benchmarked every purchase against the network's best achieved price, and handed leadership a ranked, evidence-based negotiation agenda.
Built the full historical spend cube and contract compliance tracking that strategic sourcing decisions had been missing — savings finally measured, not asserted.
Unified HR, delivery and finance systems into one semantic model and executive cockpit — ending definitional disputes and compressing leadership reporting from days to near-real-time.
Standardised incompatible product hierarchies across countries — locking definitions before pipelines — so scale-up to 26 markets became replication, not reinvention.
Integrated three proprietary systems at case level, built a supplies classification framework, and made invisible cost variability precisely quantifiable.
Designed the decision architecture that turned raw sensor data into operational recommendations and standardised ESG metrics — converting a data-collection platform into a cost-reduction product.
Built the integrated financial model — capex, unit economics, scale scenarios, sensitivities — and the stage-gated lab→pilot→commercial roadmap that made investor conversations productive.
Profiled consumers across age, ethnicity and occasion to map category value into growth spaces — turning market-share data into investment prioritisation.
All engagements delivered under NDA; client names available in private discussions. Metrics as reported in engagement outcomes.
Every capability we offer government is one we have already delivered commercially.
| Proven in the enterprise | Applied to public systems |
|---|---|
| Spend cubes, SKU benchmarking and supplier analytics | Procurement Risk Analytics & Tender Evaluation Intelligence for ministries, PSUs and oversight bodies |
| Multi-system ETL, semantic models and unified schemas | Data exchange and interoperability across departments — registries, eligibility, single-window services |
| CXO cockpits, KPI governance and adoption programmes | CM / Secretary dashboards and citizen Service Uptake Observatories with one version of the truth |
| Business cases, unit economics and stage-gated roadmaps | DPR Evaluation AI — viability, costing and phasing scrutiny for project appraisal at scale |
| Analytics training and capability transfer for client teams | Capacity building for officials and CSOs — AI and digital skills, toolkits, embedded teams |
Speaking your language
This grid doubles as a compliance matrix: for any Terms of Reference, each requirement maps to a named capability and an engagement we can cite.
Our approach
The same process that delivered our enterprise results, adapted to public governance, procurement rules and accountability.
Map the decisions, data, systems and risks that matter; agree the value case and success metrics with leadership.
Architecture, governance model, and the indicator or evaluation-lens libraries — designed with, not for, the client team.
A live solution in one or two departments with real data, measured against the KPIs agreed in the diagnostic.
Phased rollout, managed analytics services, and embedded government teams who can run the system without us.
We define the decisions and KPIs before touching any pipeline — it is why our schemas scale.
AI assists; accountable officials decide — with evidence links and audit trails throughout.
Lock shared definitions first (the 3→26 market lesson) so scale-up is replication, not reinvention.
Client teams trained to run, audit and extend every system — adoption is the deliverable.
Our team
Strategy, AI, platform delivery, capacity building and M&E — configured to the assignment, not the org chart.
Where to start
A 6–8 week, fixed-scope engagement that builds the fact base, earns trust, and produces the roadmap that funding follows.
Deploy Procurement Risk Analytics with Tender Evaluation Intelligence — the domain where our track record is strongest.
Put the flagship appraisal engine on a live approval pipeline, then extend across schemes, sectors and states as trust compounds.
We engage today with donor programmes (UNDP, World Bank, GIZ) and directly with ministries, PSUs and state departments — through fixed-scope, 6–12 week pilots on live data, priced to be sanctionable and designed to become the reference implementation.
Contact
Tell us the department, the decision you are trying to improve, and the data you already hold. We come back with a fixed-scope pilot proposal — or an honest note that it is not the right fit yet.