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Living Semantic Layer
Entities, hierarchies and metrics, defined once in business language and versioned. Every pipeline, API and AI agent reads the same definitions – so a number means the same thing everywhere.
Wekalp – the alternative to 8–10 tools per pipeline, expensive databases, intelligence you can’t audit, unexplainable data lakes, compliance fire drills, brittle ETL scripts, months-long dashboards, per-seat BI licences, six-month change requests and per-query cloud bills.
An AI-native data intelligence and automation platform
One governed platform – storage, compute, context and AI – hosted, on-premises or in your private cloud, with every solution built on top.
Built for
: Regulatory Reporting, DPDP Compliance, Audit & Lineage, Sales Intelligence, Business Intelligence, Finance Automation, Claims & Pricing Automation, Governed AI
Platform
The deterministic backbone for data automation, governance and lineage – precision, not probability
The foundation everything else runs on – one governed platform for storage, compute, orchestration and audit, so every solution and every AI answer starts from the same trusted data. It works alongside your existing systems, not in place of them.
Source Management
Master Management
Versioning & Time Travel
Query & Share
Connect & Ingest
Orchestrate & Audit
Retry & Override
Serve & Distribute
Quality & Validations
Access & Control
Lineage & Traceability
Impact & Explainability
Discover
Map
Auto-Code
Test & Deploy
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Source Management
Every load lands untouched in a raw zone, so it can be replayed from the original at any time. Quality and variance checks run before anything moves on. Failing rows are quarantined with a report, never dropped, and never hold up the rest of the load.
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Master Management
Each entity declares its key, effective date and de-duplication rule. New codes are flagged on arrival, and every description or attribute change is kept as SCD Type 2 history. Any code can be read exactly as it stood on any date.
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Versioning & Time Travel
Append-only, date-partitioned Parquet: nothing is overwritten, so any dataset can be queried as of any date. An append-only transaction log brings ACID transactions to files – atomic commits, consistent snapshots, and removed files kept for audit, never deleted.
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Query & Share
Working, curated, virtual and public datasets share one storage tier. The engine queries files where they sit and serves every consumer – pipelines, APIs, solutions and AI agents – with no cluster to size and no idle cost.
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Connect & Ingest
Ready connectors pull from files, databases and APIs. Point at a source and the platform infers its schema, types and keys for you to confirm. Loads then run on schedule, updating each destination with the load logic you define, such as transactional or positional – no code, no redeploy, and upstream changes flagged as they happen.
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Orchestrate & Audit
A built-in scheduler runs every load, transformation and output in the right order, with no third-party workflow engine to license or run. Each run is logged with its status, duration and quality result, so every step can be traced.
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Retry & Override
Failed steps retry automatically, then alert the owner. Your team can pause a run, restart from a checkpoint or approve a step before it continues. The downstream impact of every re-run is shown before it happens.
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Serve & Distribute
Governed data is served to solutions on Wekalp and to other systems through public APIs and MCP, or delivered by email, Slack and file drop in each recipient's data and delivery templates. Every delivery is access-checked and logged.
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Quality & Validations
Build your own quality rules and run them on data, versions, metrics and outputs alike. Every validation and its result is recorded against the load it ran on or the computation it belongs to.
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Access & Control
Access is set by role, down to modules, features, APIs, schemas, tables and columns. Encryption and masking on selected columns limit the blast radius of any leak, and sensitive changes go through maker-checker review.
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Lineage & Traceability
Lineage is not a feature but embedded metadata at the heart of the data store, so nothing is recalculated to produce it. Every number traces back to its origin – version, rows and columns – with a clear route map of the logic and artifacts in between.
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Impact & Explainability
Business reference tags link each data point to the metadata repository, so users see what a change or action will affect before it takes effect. Maker-checker review means a second person approves it with that impact in view.
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Discover
Point the platform at an existing workbook or workflow, and it documents the KPIs, formulas, keys and data structures inside. Changes to existing KPIs, models and templates are detected the same way, so nothing changes unnoticed.
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Map
A co-pilot proposes how source columns map to target fields, flagging matches, aliases and gaps for you to confirm. Row- and column-level changes are caught on every load, so mappings stay current without manual ETL work.
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Auto-Code
Business logic – including complex Excel formulas – is converted into versioned SQL and business rules. Every rule is tested in a sandbox before it touches live data.
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Test & Deploy
Signed-off changes move from sandbox to production as metadata, not rebuilt code, so there is no long release cycle. Every deployment is versioned and logged.
Enterprise Context
The living semantic layer beneath every AI decision
The reason AI projects stall isn't the model – it's that no system holds the context of how you actually run your business. We built the one that does.
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Usage-Driven Learning
Every question and correction teaches the layer something new. Technical logs keep each user's behaviour and past task details, so every new task starts with the context of the ones before it. Every learning can be reviewed, edited or removed.
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Multi-Source Context Enrichment
Policies, PDFs, images and notes become governed records, linked to the data they explain. Answers carry the assumptions, seasonality and exceptions behind the numbers.
AI-Native Intelligence
Insights that answer "Why," explain "How," and guide "Next"
Everything above powers this. The platform's governed data and the context layer enable intelligence and decision-making: it speaks your business language, applies the right controls on usage and access, and builds the reasoning behind every number it shows.
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Business Summarizations
Board-ready summaries tailored to what matters, configurable at any point and curated to your interests – written from the governed metrics in Enterprise Context, with every figure traced through platform lineage.
- Configurable narrative depth and tone
- Curated to user role and business focus
- Automated drivers, anomalies, and outlook
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Conversational Intelligence
Ask questions in business language. The Living Semantic Layer maps your words to the right metrics, so answers come with context, drivers and reasoning – under the same access rules as every user and API.
- Business-language inputs grounded in semantic layer
- Reasoned responses with cited drivers
- Context preserved across follow-ups
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Conversational Visualization
Generate narratives and visuals for reviews, leadership meetings and board discussions in minutes – every chart built on governed definitions, with any figure shown as it stood on any date.
- Auto-generated charts tied to semantic context
- Narrative-first framing for executive audiences
- Export-ready for review and board decks
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Text to SQL
For analysts and power users: plain language becomes SQL against the semantic layer, with full control in the SQL editor. The platform applies access rules before any query runs.
- Natural-language to validated SQL
- Inline editor with full schema awareness
- Audit-friendly query history
Technology
Speed, scale, and explainability – re-engineered for cost efficiency
Plain Parquet on your own object storage, an in-process engine with no cluster to run, security in every layer, and governed LLMs you can place anywhere – composed without lock-in, and nothing billed per credit, per seat or per query.
Open Lakehouse Storage
Plain Parquet on any object store you choose, governed by an append-only transaction log – built on Delta Lake concepts: ACID transactions, snapshots and time travel, with an audit trail on every change.
- No proprietary table format. Readable by our compute engines, queried like a database with SQL, and delivered through multiple interfaces for interoperability.
- Your store, your location. Any compatible object store, in your data centre, your private cloud or ours. Only the endpoint changes.
- Auditable by design. Every change records its author, reason, lineage and checksum – rejected writes included – and nothing is ever overwritten.
Intelligent Compute
An in-process engine, compiled per request. Heavy pipelines and quick questions run on the same engine, with no cluster to manage.
- Vectorized execution. Built on modern open-source foundations to handle complex processing at scale without performance trade-offs.
- Query-optimized orchestration and memory-efficient processing. Columnar execution, intelligent orchestration, and optimized encoding reduce compute footprint during large-scale pipeline operations.
- Formula-to-rules translation. A proprietary parser turns complex spreadsheet logic into version-controlled rules – and rules back into spreadsheet logic – for business readability.
Enterprise-Grade Security
Single-tenant by default, with security built into every layer, not added afterwards.
- Independently tested. VAPT by a CERT-In empanelled auditor, covering the OWASP Top 10, with regular reassessment.
- A dedicated instance, hosted or on-premises. Nothing shared with other customers; encrypted in transit and at rest, with a separate key per dataset.
- SSO, MFA and append-only audit. Sign-in through your identity provider, and every user and system action recorded.
AI & LLMs
Governed use of LLMs, grounded in your enterprise context and placed where your policy allows.
- Choose where the model runs. Your own GPUs, a private endpoint or a managed service. Switching is configuration, not a rebuild.
- Agents never touch raw data. They see governed metadata only, and every query they propose passes the same access checks as a user.
- Token-efficient by design. Structured, context-only prompts keep costs predictable and answers consistent.
Solutions
Packaged solutions, built on one governed platform
Every solution runs on the same platform – so the second one reuses the data, context and controls the first one built. Start with the problem in front of you; the platform grows with you.
GRC · BFSI
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Regulatory Reporting
Regulatory returns your business teams own, with every figure traced to its source and restatable as of any date. No rigid pipelines, no vendor lock-in.
GRC · Privacy
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DPDP Compliance
Find where personal data sits, take consent that stands up, and keep a hash-chained record of every action. It runs inside your own estate, without copying data out.
Business Intelligence · CPG
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Sales Intelligence & Automation
Role-specific sales intelligence built on Enterprise Context, so it mirrors your actual hierarchies and business language – not standardized dashboards.
Know more
Finance Automation · CPG
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Distributor Claims & Pricing Portal
Configurable claims and pricing workflows that cut revenue leakage and settlement cycles, with every approval and adjustment audit-ready – without disrupting distributors.
Know moreBuilding the agent is the visible 10–15% of the work. The other 85–90% – workflow decomposition, context engineering, data substrate, integration, governance – is where outcomes live or die.
We deliver both halves on a single platform we own. Storage, compute, lineage, quality, governance, and enterprise context in one box. Agents in production in under two weeks, because the substrate already exists.
A pod, defined: small, senior, forward-deployed, end-to-end accountable – with your SME embedded inside it. Not a fifteen-person factory. Not an offshore center. Not a body shop.
How the work flows
Six stages. Same pod throughout. Continuous from triage to steady state.
About Us
We believe data drives better decisions – but only when business and technology are deeply integrated
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Why we exist
Enterprises have more data than ever – across systems, teams, and channels, with rising regulatory and operational complexity.
Yet most enterprises still run on stacks built to answer "what happened" – five to eight tools stitched together, with AI now layered on top.
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Who we are
We bring 70+ years of combined experience building and operating AI, data analytics, and enterprise software in real-world environments.
We've seen what works and what doesn't – and built the platform we wished we'd had.
Wekalp (विकल्प) means “the alternative” in Hindi – and that’s what we set out to build. The “We” in Wekalp is the community we’re building around it: customers, partners and builders shaping that alternative together.
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The gap we see
Business owns the logic – but not the tools to operationalize it. Technology owns the tools – but often lacks deep business understanding.
AI layered on fragmented stacks repeats the cycle. The fix isn't another tool – it's one governed foundation both sides can own.
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Our perspective
The best systems don't just report. They explain, adapt, and guide action – answering "why" and "how," not only "what."
That's why we built the platform first: governed data, Enterprise Context in business language, and AI on top – owned by the business, run by technology.
We bring it together on one governed platform – open lakehouse storage, in-process compute and security in every layer – with Enterprise Context and governed AI on top, complementing your existing systems and evolving with your business.
Data Management
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Ingestion & Orchestration
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Governance & Audit
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Build & Change
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Enterprise Context
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Intelligence
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Reasoning
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Decision Making
The team behind Wekalp
Leadership
Testimonials
Trusted by enterprises solving complex data problems
We commit to asking the right questions – and staying accountable to deliver.
Wekalp has proven to be a trusted partner in building enterprise automation at scale, and I would strongly recommend them for organizations looking to simplify complex, high-stakes data workflows.
Chief Technology Officer
Renowned Indian Beverages Brand
The speed and agility of Wekalp's delivery have been remarkable compared to our earlier digitization efforts. For organizations weighed down by rigid technologies that fail to capture real-world complexity, Wekalp offers a refreshingly practical way forward.
Chief Finance Officer
Indian Conglomerate, Multiple Food Businesses
Resources
Practical applications, engineering notes, and playbooks
See the platform in motion.
Schedule a working session to see the governed platform – and the AI and solutions built on it – applied to a problem of yours.