Enterprise AI is being sold as agents. The 90% that determines whether those agents reach production — workflow decomposition, context engineering, data substrate, integration, governance — is left to the customer, or to someone else.
That is why 80% of enterprises now use generative AI in at least one function, and only ~5.5% report material EBIT impact.1
We invert the order. The pod builds the 90% first, on a platform we own — so the agent is two weeks at the end, not eighteen months from now.
Enterprise buyers in 2026 choose from five kinds of partner. Each is excellent at the slice they own. None is structurally able to deliver the outcome end-to-end. Wekalp is the bundle — one platform, plus the AI services that go with it.
| Partner | What they offer | Wekalp — Platform + AI Services, in one box |
|---|---|---|
| Cloud-scale lakehouse incumbents | Storage + compute. You assemble the catalog, lineage, quality, governance, context, agent runtime — and find the pod yourselves. | Lakehouse + every layer above it, native in one box. Plus the pod that builds on it, end to end. |
| Best-of-breed catalog, quality, and transformation specialists | One slice each. You stitch together five other tools, the integration tax, and the agent layer entirely. | Every slice native, in the same box. Plus the pod that owns the substrate. |
| Pure-play AI delivery firms · new-wave agent specialists | A pod that ships agents on a data substrate they assume already exists. Most pilots quietly stall there. | The substrate is the box — purpose-built for agents. The pod ships them in < 2 weeks. |
| The global systems integrator majors | Implementation hours and a managed services tower — on top of the same six-vendor stack you'd be licensing anyway. | One platform replaces the stack. The pod is priced to the outcome, not to the hours. |
| Hyperscaler-native AI platforms | Credits, models, tooling — and no opinion on your workflow. You bring the pod. | Models routed through governed enterprise context. The pod brings the workflow. |
Against a typical six-vendor stack assembled for equivalent scope: Wekalp delivers a 30–40% reduction in three-year TCO — before counting the SI hours not needed for the assembly.
Wekalp is a Data Platform + AI Services company. Sold as one bundle — not two line items. Both halves are designed for each other.
Single-box. AI-native. Storage to agent runtime — natively integrated.
A small, senior pod — forward-deployed, end-to-end accountable, with your SME embedded inside it.
The only credible answer to "who owns the outcome end-to-end" is a partner who owns both the platform and the pod.
Traditional enterprise software splits delivery into discovery, implementation, and managed services — with separate teams, separate contracts, and a fifteen-person factory between you and the outcome. We collapse that into four stages, with the same five-person pod throughout.
A 45-minute working session against one of your in-flight workflows. We tell you which parts should and should not be agents. You walk away with a one-page triage map and an outcome estimate.
A 2–3 week sprint. Our accelerators ingest the artifacts the business already runs on — spreadsheets, reports, SOPs, mail trails — and reverse-engineer the workflow, the substrate, and the decision logic.
Every workflow has two parts. The traditional layer is auto-coded by our accelerators — the pod hand-writes no automation. The agentic layer is assembled from our agent library, then tweaked to fit your context.
Agents in production in under two weeks each. Any incremental code stays small, focused, and ours to maintain — never a codebase you inherit.
Same pod, sized down. The platform absorbs the technical operations. Customizations are delivered as agents — incremental change requests answered in hours and days, not in change-request cycles.
This structure is incompatible with the SI model — which depends on a contract boundary between implementation and managed services. It is incompatible with the FDE shop model — which has no platform underneath to make 2-week delivery credible. It is incompatible with the platform vendor model — which has no pod. That is by design.
Every gravel road we walk in a client engagement is paved into a reusable highway. Our accelerators encode that institutional muscle. They are why our delivery economics work — and why the 2-week claim is industrialized, not heroic.
Ingests the spreadsheets, reports, SOPs, and email trails the business actually runs on. Reconstructs the decision logic, branching rules, exception flows, and approval ladders no one documented.
Walks source systems — ERPs, core banking, OMS, warehouses — infers entities and relationships, classifies attributes, and surfaces master-data conflicts before they hit production.
Builds the living semantic layer — business definitions, KPI logic, relationship graph, glossary — that an agent reads to know what the business actually means by "active customer" or "regulatory exposure."
Takes the as-is workflow, the substrate readiness, and the quadrant triage, and outputs a phased digitization roadmap — what becomes a workflow, what becomes an agent, what stays human-in-the-loop, with effort and dependencies named.
Generates ingestion, transformation, orchestration, and lineage instrumentation on Wekalp's platform. AI-drafted, engineer-validated, deployed in days.
Pre-built templates per workflow pattern — regulatory commentary, claims triage, exception routing, distributor reconciliation, sales-call brief — pre-wired to evaluation, lineage, and the consumption layer.
The agent is only as useful as the interface your business actually uses every day. We give you two options. Both run against the same substrate, the same context, the same lineage.
Your team is already in Claude or ChatGPT. We expose Wekalp's enterprise context, governed data, and agent capabilities as MCP servers. Users get authorized, lineage-backed answers — without leaving the assistant they already use. Identity flows through. Permissions are honored. Every answer is traceable to the row of data it came from.
For teams that need a controlled enterprise interface — audit trail, role-based access, data residency inside your own VPC — Wekalp provides a turnkey conversational front end on the hyperscaler your enterprise has standardized on: Amazon Bedrock, Google Vertex AI, or Azure AI Foundry. Model-agnostic. Governance in the loop. Deployed inside your perimeter.
Forty-five minutes against one of your in-flight workflows. We tell you which parts should and should not be agents. You walk away with a one-page triage map, an outcome estimate, and zero obligation either way.