AI Analytics & Insights Services — from raw data to board-ready answers
Turn spreadsheets and siloed systems into real-time dashboards and natural-language insights. We unify data, add governance, and deliver a BI copilot your teams will actually use.
Why analytics stalls — and how we unlock fast, governed insight
From spreadsheet chaos and stale reports to real-time, trusted answers via an AI analytics copilot.
Where teams get stuck
-
Data scattered & inconsistent
Sheets, CRM, ERP, ads, and custom DBs don’t align. Definitions vary by team. -
Slow reporting
Analyst bottlenecks create week-long waits. Decisions rely on stale snapshots. -
Governance gaps
No row-level controls, weak lineage, and ad-hoc access — risk increases with scale. -
Low adoption
Dashboards are hard to find, harder to use, and never answer “my specific question”.
How we solve it (fast)
-
Unified model & pipelines
Connect BigQuery/Snowflake/Sheets; define metrics in one semantic layer. -
AI analytics copilot
Ask in EN/HI → get charts, tables, and CSVs. Analysts focus on deep dives. -
Governance by design
SSO, RBAC with row-level security, masking/redaction, lineage & audit logs. -
Live KPI dashboards
Define north-star metrics; track conversion, CAC/LTV, churn, collections in real time.
Analytics services that turn data into decisions
End-to-end: integration → semantic layer → governance → NLQ copilot → live KPIs.
Data Integration & Pipelines
Connect CRMs, ERPs, ads, databases, and spreadsheets into a reliable warehouse.
Metric Layer & Modeling
Define a single source of truth for KPIs and dimensions across teams.
Data Governance & Security
Access that fits your org chart, with auditability and redaction where needed.
Natural-Language Analytics Copilot
Ask in EN/HI and get dashboards, tables, and CSVs — with citations back to the source.
KPI Dashboards & Alerts
Board-ready views for revenue, funnels, collections, retention — refreshed in real time.
Training, Playbooks & Change
Role-based workshops, data glossary, and SOPs so teams adopt self-serve analytics safely.
From messy data to trusted answers — in 6 steps
Timeboxed delivery with clear KPIs. Typical pilot goes live in 2–6 weeks.
Implementation timeline
1) Audit & Alignment (Week 0)
Inventory sources, map KPIs, confirm governance goals, pick 2–3 high-ROI use cases.
2) Connect & Model (Week 1)
Set pipelines to BigQuery/Snowflake; define a semantic layer for metrics & dimensions.
3) Governance (Week 1–2)
Enable SSO, RBAC with row-level security, masking/redaction, and audit logs.
4) Copilot (Week 2–3)
Launch NLQ analytics copilot (EN/HI) with query audit trail and citations to source.
5) Dashboards & Alerts (Week 3–4)
Ship board-ready KPIs: funnels, cohorts, CAC/LTV, collections; set Slack/email alerts.
6) Enablement & Handover (Week 4+)
Train roles, finalize glossary & SOPs, and set improvement cadence.
Outcomes your leadership will love
Faster decisions, higher adoption, stronger governance — with KPIs tracked live from day one.
“Answers in minutes, not days.”
Sales, churn, and collections queries now happen via natural language; analysts focus on strategy.
Risk-reversal promise
If pilot KPIs don’t move, we extend two weeks at no charge and adjust prompts/model mix until metrics shift — or you don’t continue.
* KPI ranges are typical for successful pilots; actual results vary by data quality, baseline, and scope.
Recent data wins
Fictionalized but representative outcomes for analytics & insights deployments.
Natural-language insights for sales & collections
Execs query churn, cohorts, and risk in EN/HI; CSV exports auto-sent to teams.
Funnel & cohort KPIs in real time
Unified ads + CRM + orders; alerts for CAC spikes and stockouts.
Row-level security & lineage across BI
SSO, masking/redaction, and metric contracts cut access risk and KPI drift.
Quality & inventory KPIs unified
Incremental CDC pipelines; anomaly alerts for rejects & delays.
Simple pricing for analytics — fast payback
Model/API usage at cost. We align scope to your KPIs and data realities.
Data Audit & Pilot
Validate value fast with 1 KPI dashboard or NLQ use case.
If KPIs don’t move, we extend 2 weeks free.
Growth Insights
Scale across teams with multiple sources, dashboards, and NLQ.
We adjust model/pipelines free if KPIs lag.
Enterprise Analytics
For sensitive workloads with strict governance and controls.
We prepare assessment docs & reviews.
* Prices exclude API/model usage where applicable. GST extra. Scope tailored to your stack & KPIs.
Still on the fence?
Straight answers on data effort, models, governance, cost, and change management.
How much data work is needed before we see value?
We start with a thin slice: connect 1–2 sources, model a handful of KPIs, and launch an NLQ copilot for your top questions. Typical pilots show value in 2–6 weeks.
Which models/BI tools do you support?
We’re tool-agnostic: BigQuery/Snowflake/Postgres, Looker/Tableau/Power BI, and LLMs (OpenAI, Anthropic, Google, Llama/Mistral, or local/Ollama). We choose based on accuracy, latency, and cost.
Is our data secure and compliant?
Yes — SSO, RBAC with row-level security, masking/redaction for PII, and full lineage/audit logs. We can deploy in your VPC/on-prem if required.
What does ongoing cost look like?
Our fees are fixed-scope; model/API usage is billed at cost. We tune prompts/model mix and caching to keep run costs low while hitting KPIs.
Will this replace analysts?
No — it removes queue work so analysts focus on deep analysis and experiments. Clear escalation paths and approvals stay in place.
How fast can we roll this out across teams?
After the pilot, additional teams typically onboard in 1–3 weeks each, since the metric layer and governance are reusable.