IBM-powered Agentic AI services.
From IBM software evaluation to production-grade Agentic AI workflows and modernized analytics, Incede.ai supports enterprise teams across discovery, demo, pilot, implementation, governance, integration, and ongoing support.
10+ years · 200+ enterprise customers · Silicon Valley HQ · Global delivery across North America & APAC
Services built around the Agentic AI lifecycle.
Each offering maps to a clear path from use case to governed production: Discover · Pilot · Productionize · Scale. During Discovery, we define the workflow, systems, governance needs, success criteria, delivery sequence, and pricing before implementation begins.
Agentic AI Discovery
Identify high-value workflows, business outcomes, systems, data needs, and implementation requirements before build begins.
Demo and Pilot Development
Build practical IBM-powered demos and pilots tied to real workflows, stakeholder priorities, and enterprise data patterns.
Enterprise Integration
Connect AI agents to systems of record, databases, documents, applications, and workflow tools across modern and legacy environments.
Governance and Compliance
Design approval flows, auditability, access controls, observability, policy controls, and human review into the deployment.
Production Deployment
Move pilots into reliable, scalable enterprise environments with identity, runbooks, monitoring, and operational handoff.
Managed Support
Provide post-launch optimization, adoption support, training, monitoring, enhancement, and ongoing delivery support.
Explore how we deliver.
watsonx Orchestrate implementation
Prebuilt and custom agents, multi-agent workflows, enterprise integration, and the Agent Control Plane.
Explore →Agentic AI governance
Identity, audit trails, evaluation, guardrails, and observability with IBM watsonx.governance.
Explore →Implementation methodology
Our Discover → Pilot → Productionize → Scale model, from use case to governed production.
Explore →Data to decision, on one governed foundation.
Most engagements start with an agent or an analytics use case. For large organizations standardizing their data estate, we also bring IBM watsonx.data — the open lakehouse layer beneath it all — so agents, analytics, and governance all run on the same trusted data.
Data foundation
watsonx.data
Open, hybrid lakehouse over your existing warehouses and lakes. Governed, query-in-place data for every agent and dashboard — built on open formats, deployable on cloud, hybrid, or on-prem.
Agents & AI
watsonx Orchestrate · watsonx.ai
Agentic workflows and foundation models that act on that data across your systems — including vector grounding (RAG) sourced from the lakehouse.
Analytics
Cognos · Planning Analytics · watsonx BI
Trusted BI, planning, and natural-language insight on the same governed data your agents use.
Governance
watsonx.governance
Policy, lineage, audit trails, and safety controls spanning every layer — data, agents, and analytics.
watsonx.data is a complementary, foundation-layer capability — added when your data estate calls for it, not a prerequisite to start.
Modernize trusted analytics with AI-assisted insight.
We help enterprises modernize BI, planning, reporting, and forecasting environments, moving from static dashboards to trusted, AI-assisted insight while improving governance, visibility, and decision support.
Cognos Analytics
Self-service BI and reporting at enterprise scale. We modernize Cognos environments and integrate AI assistants for natural-language insight.
Planning Analytics
The TM1-based platform behind much of the enterprise planning layer. We migrate, modernize, and AI-enable existing deployments.
watsonx BI
AI-native business intelligence. Natural-language Q&A on your governed data — for teams that want answers, not dashboards.
Flexible ways to start, built for production.
Incede.ai supports fixed-scope pilots, phased implementations, and ongoing managed support. During Discovery, we align on the right model for your use case — including scope, deliverables, timeline, integration requirements, governance needs, success criteria, and support plan. Whether you are validating a first workflow or scaling an existing deployment, our delivery model is designed around adoption, operational readiness, and long-term value.
Fixed-scope pilot
Validate one bounded workflow
Working pilot with success criteria and production-readiness findings
Phased implementation
Move from pilot to governed production
Integrated, governed workflow with runbook and operational handoff
Managed support
Optimize and expand after launch
Monitoring, tuning, governance reviews, adoption support, and enhancement backlog
“Incede.ai earned our trust by bringing not only deep technical expertise, but a level of thoughtfulness and partnership that is rare. They didn’t approach this as a vendor delivering a solution; they operated as an extension of our team.”
Services FAQ.
Do you have a prebuilt agent catalog?
Yes. Our prebuilt agent catalog spans HR, Sales, Procurement, Customer Care, IT, Productivity, Finance, Legal, Marketing, and Supply Chain — configurable accelerators on IBM watsonx Orchestrate, designed for rapid customization to your systems of record and governance model.
Can you build custom agents for workflows that aren't in the catalog?
Yes. We do custom agent development on watsonx Orchestrate and watsonx.ai for any workflow we don’t already cover — co-designed, co-built, and handed over with the runbook your team owns.
Do you support multi-agent workflows?
Yes. We design multi-agent workflows where multiple agents collaborate across departments and systems to complete an end-to-end process — orchestrated, observable, and governed as one workflow rather than a collection of disconnected bots.
What does universal enterprise integration mean in practice?
Our agents integrate with any ERP, CRM, HR system, IT service management tool, or document repository — modern or legacy — through native APIs where they exist and RPA or file-based bridges where they don’t. Every bridge runs under the same policy, audit, and observability layer as the rest of your agentic estate.
Can you integrate with our ERP and finance systems?
Yes — SAP, Oracle, Microsoft Dynamics, Workday Financials, and NetSuite are the most common, plus any other ERP or finance system with an API or supported bridge.
Can you integrate with our CRM and customer platforms?
Yes — Salesforce, HubSpot, Dynamics CRM, Zendesk, and ServiceNow CSM are common, alongside other CRM and customer-experience platforms.
Can you integrate with our HR, ITSM, and collaboration tools?
Yes — Workday, SuccessFactors, ServiceNow, Jira, Okta, Microsoft 365, Google Workspace, and Slack are commonly integrated, along with other HR, ITSM, and collaboration systems.
Can you integrate with our databases, warehouses, and document repositories?
Yes — DB2, Oracle, SQL Server, SharePoint, Box, and Confluence are common targets, alongside other databases, data warehouses, and document repositories.
Can you integrate with mainframe, terminal, and legacy core systems?
Yes — z/OS, IBM i, CICS/IMS, 3270/5250 green-screen, and banking, insurance, and healthcare core systems are all supported, typically through screen-scraping, message bridges, or supported APIs.
What if direct integration isn't available?
We use RPA or file-based bridges — IBM RPA, UiPath, Automation Anywhere, Power Automate, and SFTP/EDI/CSV exchange — to connect systems that don’t expose APIs. The bridge runs under the same governance, audit, and observability layer as native integrations.
How long does it typically take to go from use case to production?
Most first workflows move from discovery to governed production in 4–12 weeks, depending on integration depth and data readiness. We start with a bounded use case — one workflow, one team, measurable baseline — then expand as adoption stabilizes. Timelines vary with executive sponsorship, IBM software entitlements at kickoff, and the complexity of the systems involved.
Do you provide post-launch support and managed services?
Yes. We stay engaged after launch with managed support for monitoring, agent tuning, governance reviews, model lifecycle updates, and ongoing optimization. Most customers continue with us into a steady-state operating model — expanding to additional workflows once the first one is live and trusted.
Can the platform run on our own cloud or on-prem?
Yes. We deploy across IBM Cloud, AWS, Azure, Google Cloud, hybrid, and on-premises — cloud-native, containerized, and audit-trailed. watsonx supports on-prem, sovereign-cloud, and OpenShift deployments for regulated jurisdictions or data-residency requirements.
Do you work with IBM watsonx.data?
Yes. watsonx.data is IBM's open, hybrid data lakehouse — the governed data foundation beneath Agentic AI and analytics. We bring it in where large organizations need a single, open layer to access and govern data across existing warehouses, lakes, and operational systems, and to feed trusted data to agents (including vector/RAG grounding) and to BI and planning. It's a complementary, foundation-layer capability: most engagements start with a workflow or analytics use case and add the data layer when the data estate calls for it.
How does watsonx.data compare to Snowflake or Databricks — and can it work alongside them?
It can do both. watsonx.data is an open lakehouse built on open table formats such as Apache Iceberg, with multiple fit-for-purpose query engines. Because it's open-format, it's designed to query data in place across existing platforms — including Snowflake and Databricks environments that expose open formats — rather than forcing a rip-and-replace migration. So for many enterprises it's complementary: keep your current warehouse or lake and use watsonx.data as the open, governed access layer that unifies them and feeds IBM watsonx.ai and Agentic AI. Where it is evaluated competitively, IBM's emphasis is openness and no vendor lock-in, hybrid and on-premises deployment for data-residency and regulated workloads, and native integration with watsonx.governance for lineage and policy. We help you decide where each platform fits rather than push a single answer.
Do we have to replace our existing data warehouse or lake to use IBM AI?
No. Our agents and analytics integrate with the databases, warehouses, lakes, and document repositories you already run. watsonx.data is optional — an open lakehouse layer you add when you want unified, governed access across a fragmented data estate. We design the data foundation around what you already operate, not a forced migration.
How is sensitive data and PII handled?
PII can be kept within your tenant and VPC through architecture design. We apply redaction before any fallback model call, retain full lineage on every prompt and response, and align controls to SOC 2, HIPAA, and FINRA expectations. Data classification and retention follow the policies your team already operates under — we don’t introduce a second governance regime.