MIDAS unifies all your marketing data, models it with AI, and turns insights into recommended actions. You stay in control — nothing runs without your approval. Intelligent automation with a human in the loop, across all three layers, live now.
Ten platforms. Ten dashboards. Each claiming credit. Problems found the next morning. Decisions starting from scratch every time. Hours between insight and action.
All three layers are live. Start with intelligence. Add decision automation. Enable autonomous execution. Each layer compounds the value of what came before.
Unified data from 15+ channels. Attribution, anomaly detection, lead scoring, competitive intelligence. Dashboards by 8am, every morning.
AI diagnoses, recommends, and presents structured actions. You approve quickly. System executes precisely. AI learns from every decision.
For action types where preferences are fully calibrated, execution becomes autonomous within the limits you define. The full loop — closed. You stay in control of every boundary.
MIDAS delivers the full loop: intelligence every morning, AI-recommended actions for your approval, and autonomous execution of trusted actions — all as a managed service.
White-label the full three-layer MIDAS stack under your brand. Every client decision builds a preference profile that makes switching providers genuinely costly — not through contracts, through compounding value.
Six production-grade components orchestrated into one closed intelligence pipeline. From data collection through to autonomous channel execution — private VPS, local AI inference, data sovereignty by design.
Each layer builds on the last. Together they form the first fully integrated intelligence-to-execution system for marketing teams that want to stay in control while moving at AI speed.
Six proven, production-grade open-source components. Private VPS. Docker containers. Every component auditable, every one under our operational control.
| Component | Role | What It Does in MIDAS | Proven at |
|---|---|---|---|
| n8n | Orchestration | Workflow automation. 400+ platform integrations. Manages all data collection, AI task routing, approval orchestration, and channel execution across all three layers. | Airbnb, Delivery Hero |
| KNIME | Analytics | Data science platform. Runs attribution, anomaly detection, lead scoring, LTV prediction, and audience segmentation. Also generates pre-execution validation checks for Layer 3. | 1M+ data scientists globally |
| PostgreSQL | Warehouse | Central data warehouse and system of record. Raw data, modelled outputs, AI context, approval decisions, execution logs — all in one place. Row-level security for client isolation. pgvector for semantic AI memory. | Apple, Spotify, Instagram |
| Ollama | Local AI | Runs open-source LLMs locally. Classification, embeddings, summaries, approval routing logic — no external data routing for these high-frequency tasks. Zero marginal cost at volume. | Enterprise AI deployments |
| Claude | Frontier AI | Complex attribution interpretation, strategic recommendations, nuanced insight narratives, content generation. Enterprise API — no client data used for model training. Minimum data per call. Quality-critical outputs that shape client decisions. Human review before delivery. | Enterprise AI deployments |
| Apache Superset | Dashboards | Client-facing BI dashboards with role-based access. Serves Layer 1 intelligence, Layer 2 recommendation status, and Layer 3 execution reports — all from the same data source. | Airbnb, Lyft, Twitter |
| Caddy | Gateway | Secure, automatic HTTPS gateway. Sole external-facing component. Auto-provisions TLS certificates, handles rate limiting, IP access controls, and routing to internal services. All other components sit behind it, invisible to the internet. | Used in production deployments globally |
The intelligence foundation. Every channel unified, every model running, every insight surfaced — automatically, every morning before 8am. The layer everything else is built on.
Paid media, organic content, email, SEO, CRM — Layer 1 unifies intelligence across every channel, including a dedicated content marketing intelligence module.
Google Ads, Meta, LinkedIn, GA4, HubSpot, Salesforce, email, SEO, social — one consistent model across every source, updated daily. Our orchestration engine (n8n) has 400+ native integrations.
Multi-touch attribution built across all channels including content. Which blog posts, social series, and downloadable assets are actually driving revenue — not just traffic. Often dramatically different from what platforms claim.
Continuous monitoring across paid and content channels. CPA spikes, budget pacing, creative fatigue, content engagement drops — flagged the moment they emerge with plain-English diagnosis.
AI models trained on actual CRM deal outcomes. Lead scores written directly to HubSpot or Salesforce in real time — including which content assets each lead consumed on the path to conversion.
Which blog posts, social content, and downloadable assets are generating qualified leads? Content attribution connects every asset to business outcomes. Pillar balance monitoring, SEO gap analysis, competitor content tracking, and optimal posting time signals — in one unified view.
Competitor search rankings, ad activity, and content publishing monitored continuously. Share-of-voice trends, keyword gaps, topic gaps, competitor content performance — surfaced proactively.
Apache Superset dashboards refreshed daily. Paid performance, content performance, attribution, lead scoring — unified in one role-based view. Each person sees exactly the level of detail they need.
Google Ads, GA4, Search Console connected. First dashboards live. Paid & organic intelligence active.
Meta Ads & CRM connected. Cross-channel attribution active. Lead scoring operational.
Email, competitive intelligence, content performance. Full channel coverage at full depth.
Intelligence baselines established. AI preference profile begins. Ready to activate Layer 2 decision automation.
Layer 1 gives you the intelligence. Layer 2 turns it into approved action.
Intelligence becomes action. AI identifies what should change, drafts a structured recommendation with full reasoning, and presents it for your approval. The system executes exactly what you approved.
Continuous monitoring spots a CPA problem, budget pacing issue, or opportunity the moment it emerges — not the next morning in a report.
AI diagnoses the cause and drafts a specific recommendation — the situation, the reasoning, the proposed action, the expected outcome, and the confidence level.
Structured recommendation delivered to the right approval channel — Slack for operational decisions (2hr target), Notion for strategic ones (24-48hr review cycle). Covers both paid media and content decisions.
Four options: Approve, Reject, Modify, or Defer. Nothing executes without your say. The Modify option teaches the AI your preferred scale and style.
Approved actions execute precisely — budget adjusted, lead scored, content scheduled. Every execution includes pre-validation, spend cap checks, and full logging.
Outcomes tracked against predicted results 48-72 hours later. What worked improves the next recommendation. A growing library of evidence that the service actually delivers.
A recommendation that contains only "do X" invites blind approval or blind rejection. MIDAS presents every recommendation with full reasoning — so you can assess the logic, not just the conclusion.
The same six-component recommendation structure (situation / diagnosis / action / expected outcome / confidence / expiry) applies to content marketing. AI identifies what your content strategy should change — you approve in Notion, system executes.
AI detects that educational content is 18% of your published mix vs. a 35% target, while promotional content is over-represented. Recommendation: shift the next 3 scheduled posts to educational format.
AI detects a keyword your competitor ranks in position 3 for, that you have no content targeting. Estimated search volume and difficulty supports a recommendation to create a targeted blog post.
AI detects that your LinkedIn audience engagement peak has shifted from 9am to 7pm over the past 30 days. Current posting schedule is misaligned. Recommendation: update schedule to match actual audience behaviour.
Layer 2 gives you approved action — for both paid media and content. Layer 3 closes the full loop.
The full loop — closed. For action types where your preferences are fully calibrated through Layer 2, execution becomes autonomous within the limits you define. You stay in control of every boundary. The system works within them — continuously, precisely, without delay.
Layer 3 is not "remove the human." It is "the human has already established, through months of Layer 2 decisions, what types of actions can execute automatically — and within what parameters." Autonomy is earned through calibration, not assumed from day one.
Every piece of content published through Layer 3 generates performance data that flows back into the next content brief. Over time, your content strategy is shaped by evidence — not assumptions.
When AI drafts a content brief, it queries the performance history of every previous brief with similar parameters — topic, format, pillar, tone. The brief is informed by what has actually worked for this client, not generic best practice.
The system tracks which content formats (case study, how-to, opinion, data piece) and which pillars (educational, promotional, community) are generating the best business outcomes for each client — and weights future content recommendations accordingly.
When a blog post performs above its baseline in organic search, Layer 3 automatically recommends (or in autonomous mode, creates) a social series adapting its key points. High-performing content compounds — it does not stop working after it is published.
Layer 3 is not free-running automation. Every autonomous execution — however routine — passes the same five-stage validation sequence. Safeguards are never optional, never skippable.
Checks client-defined spend limits before every paid media execution. If the action would exceed the cap, it aborts and raises an alert.
No single autonomous action can change a budget or bid beyond defined percentage and absolute limits — even if the recommendation called for more.
Confirms current campaign state matches expected state before making any change. Manual modifications between recommendation and execution trigger abort.
Checks whether the action has already been executed before any retry. The same action is never applied twice due to a technical retry or system error.
Every action is logged — before the external call and after the result. Success or failure, platform confirmation or error — all recorded with timestamp and approver context.
Layer 3 autonomy does not begin on day one. It is the result of Layer 2 calibration — months of approvals and rejections that establish, precisely, what this client is comfortable delegating and within what limits.
Human approves every recommendation. AI builds preference profile — thresholds, magnitudes, timing, brand constraints.
For action types with 80%+ approval rate and consistent parameters, client can activate autonomous execution — with explicit limit definitions.
Autonomous execution within client-defined limits. Human oversight via daily digest and real-time alerts. Override available at any time, instantly.
MIDAS is the only fully integrated intelligence-to-execution system built for marketing teams that want to stay in control while moving at AI speed.
MIDAS gives you the complete loop — from unified intelligence to autonomous action — as a fully managed service. No data scientists. No infrastructure. No platform logins.
Every channel in one view by 8am. True cross-channel attribution. AI anomaly alerts in real time. Lead scoring to your CRM. Competitive intelligence. Plain-English insight summaries.
AI diagnoses, recommends with full reasoning, and presents for your approval. Approve quickly. System executes exactly what you approved. AI learns from every decision.
For trusted action types, execution runs autonomously within limits you define. Budgets adjusted, leads scored, content scheduled — continuously, without delay. Every action logged and reported.
Local AI inference for routine tasks — no data leaves your environment. Full client data isolation at database level. Immutable audit trail of every action. Data residency options available.
Lead scoring calibrated on actual CRM deal outcomes. Attribution connected to revenue, not just conversions. Budget decisions based on which channels produce your highest-value customers.
We connect all platforms, run all models, configure all workflows, and deliver all outputs. Your team receives intelligence and acts on it. No infrastructure, no engineering, no maintenance.
All channels connected. Dashboards live. Attribution, anomaly detection, lead scoring fully operational.
AI recommendations begin flowing. Approval channels configured. Preference profile starts accumulating from your first decision.
For action types with mature preference calibration, autonomous execution activates within your defined limits.
80%+ approval rate. Deep institutional knowledge. Autonomous execution across all trusted action types. Intelligence that genuinely thinks like you.
That is what MIDAS delivers across all three layers — fully managed, fully controlled by you.
White-label the complete three-layer MIDAS stack under your brand. Intelligence. Decision automation. Autonomous execution. Every client decision builds a preference moat no competitor can replicate without starting from scratch.
Unified data from 15+ channels — paid, organic, content, email, CRM. Attribution across all channels including content assets. Lead scoring, anomaly detection, content pillar analysis, competitive intelligence. All under your agency brand — MIDAS is invisible to your clients.
Your branded Slack and Notion workspace. Clients approve AI recommendations — paid media and content strategy. Your agency's name on every recommendation, whether a budget shift or a content pillar rebalancing.
For clients with mature preference profiles, autonomous execution within defined limits runs continuously under your service umbrella. Daily digests and execution reports carry your brand.
New monthly revenue layered on existing billing. Layer 1 analytics tier. Layer 2 automation tier. Layer 3 autonomous execution tier. Each layer adds incremental recurring revenue per client.
After 12 months, your client's preference profile — 25-40 calibrated preferences, accumulated outcome history, semantic content library — belongs to your engagement. A competitor starting fresh cannot replicate it.
We manage all platform integrations, data pipeline setup, dashboard configuration, and workflow builds. Your team focuses on the client relationship. No data engineering skills required.
MIDAS adds a new recurring revenue stream on top of your existing client billings. The platform is priced so partners capture 30–50% margin on the analytics and automation tier. Each additional layer activated per client adds incremental recurring revenue. As your client base scales, partner cost per client reduces — expanding margin further.
Preference learning profile. Outcome history library. Approval rate trajectory. None of these transfer to a new provider on day one — they require months to rebuild.
Once a client has autonomous execution configured for their trusted action types, the cost of switching is not just losing intelligence — it is losing operational continuity that has been running their campaigns.
Three steps: Partner Call → Live Demonstration → First Client Pilot.
Every component is production-grade, widely deployed, and completely under our operational control. No vendor lock-in. No third-party data routing. No black box in the middle.
Security in MIDAS is not a compliance checkbox. It is a consequence of how the architecture is designed — from network isolation to immutable audit trails across all three execution layers.
PostgreSQL, n8n, KNIME, and Ollama live on Docker's internal network — unreachable from the internet. Caddy is the sole, controlled entry point to the entire stack.
All communication HTTPS-encrypted via auto-renewing Let's Encrypt TLS certificates. No data transmitted in plain text at any point between users and the platform.
PostgreSQL row-level security enforces that one client's data can never appear in another's query or dashboard — enforced at database level, not application code.
Role-based access in Superset per user. IP restrictions on admin interfaces. API credentials stored securely — never exposed in logs, dashboards, or error messages.
Ollama runs all high-frequency AI tasks locally. Classification, embeddings, tagging, approval routing — no data leaves the server for these tasks. Zero external routing at any volume.
Every data load, AI inference, human approval, and Layer 3 autonomous action is logged in an append-only record. Complete forensic history — including every autonomous execution.
The entire MIDAS platform — all three layers — runs on a dedicated VPS in a professional data centre. No co-mingling with other tenants. No data routed through third-party analytics platforms.
Your data processed where you control access, retention, and processing — not inside a third-party analytics cloud. This applies to all three layers including execution logs.
Ollama runs AI inference within the same infrastructure as the data. High-frequency tasks across Layers 1, 2, and 3 never require external API calls — zero marginal cost at scale.
Container-based deployment means the platform can run in any geography for data residency requirements. Relevant for clients in EU, India, and regulated markets.
All three layers of execution — collection, approval, autonomous action — are within the same controlled environment. No execution handoffs to external orchestration systems.
Two AI tiers matched to task type. High-frequency tasks run locally at zero cost. Complex strategic analysis routes to frontier models where quality determines client outcomes.
Layer 1: content classification by pillar/tone/intent, embeddings, anomaly summaries. Layer 2: recommendation routing, approval formatting for both paid and content decisions. Layer 3: pre-execution validation, content brief quality checks, execution log processing.
Complex attribution interpretation, strategic recommendations, nuanced insight narratives, content generation. Enterprise API — no client data used for model training. Minimum data per call.
Two audiences, two sets of questions. Select your category below. If you don't find what you're looking for, book a call and ask us directly.
Book a call and ask us anything directly. No scripts, no sales pressure — just honest answers about whether MIDAS is right for your situation.
MIDAS is not a startup idea. It is what fifteen years of solving real marketing data problems looks like when it becomes a product — built by NettScience, a Bengaluru-based Marketing Data Science Agency.
NettScience was founded in 2009 in Bengaluru, serving clients across industries in India and around the world.
Our capabilities span the full range of modern marketing intelligence — from marketing strategy, research, and statistical modelling through to data visualisation, ML, AI, and data engineering:
Predictive modelling, customer insights, marketing effectiveness measurement, and financial analysis.
Campaign analytics, attribution modelling, customer journey insights, SEO and content analytics.
Qualitative and quantitative methods, consumer insights, competitive intelligence, and opportunity assessment.
Tailored dashboards and interactive reports in Power BI, Tableau, and Apache Superset that simplify complexity and give teams real-time visibility.
Our mission is to equip SMEs and agencies with the insights to make smarter decisions, sharper strategies, and stronger ROI. By combining advanced analytics with deep domain expertise, we turn data into a sustainable competitive advantage — and build the trusted partnerships that make it last.
Predictive models, market intelligence, and ROI frameworks that turn complex data into strategic clarity.
Go-to-market strategies, market entry roadmaps, and positioning grounded in data-driven intelligence.
Churn modelling, predictive lead scoring, and lifecycle optimisation that maximise customer LTV.
Journey mapping that surfaces friction, drop-off, and high-intent moments across touchpoints.
Data-driven campaigns from segmentation and creative strategy through to measurement and attribution.
Every client we worked with had more data than they could make sense of. And every engagement repeated the same manual cycle: define goals, collect data, engineer and transform it, run EDA, build the data and ML models, assemble dashboards, prepare presentations. Hours of hand-assembly before anything useful emerged.
We built attribution models manually. We wrote anomaly-detection scripts. We assembled recommendation frameworks by hand. The results were consistently valuable — but the process was slow, expensive, and never continuous. Worse, there was no institutional memory: the history lived only in the analysts' heads.
MIDAS turns that end-to-end marketing data science workflow into a system. The process is faster and consistent, the memory belongs to the organisation rather than individuals, and it improves with every cycle.
Platform-reported attribution is systematically biased. Every platform overstates its contribution. We built cross-channel attribution models for clients for years. MIDAS runs them automatically, every morning.
Most marketing teams have plenty of data but almost no unified intelligence. The gap between data and intelligence is exactly what MIDAS fills — automatically, across all channels simultaneously.
By the time a report surfaces a problem, conditions have changed. MIDAS detects anomalies in real time, drafts a structured recommendation, and presents it for approval — before budget is wasted.
MIDAS was built by analysts who have solved these problems for real clients across fifteen years. Every model, every recommendation structure, every dashboard reflects that depth.
Complete structure for the MIDAS subdomain — all three layers live. Every page, its purpose, primary audience, and conversion goals. Build in the sequence numbered below.
Primary action for businesses. Calendly embed on contact page. In nav, hero, every page CTA band.
Primary action for agencies. Form or Calendly. In nav, hero, For Agencies page, Partner Programme page.
Mid-funnel gated PDF. Three variants: Client Brief, Agency Brief, Architecture Brief. Email capture. On hero and audience pages.
High-intent. Form with scoping questions. In nav (secondary), pricing page, contact page.
Agency-specific high-intent. Partner Programme page. Application form capturing agency size, client mix, and first client candidates.