Agents act as a user, inside that user's permissions.
Systems of record, not exports and sandboxes.
Golden sets and regression gates before release.
Every step, tool call and decision, retained.
Checkpoints, escalation, override and reversal.
Captured before we write code.
The pilot is 10% of the work.
The distance between a working demo and a production enterprise system is not model quality. It is eight missing layers, and most teams discover them after the budget is committed.
- A model API key
- Prompts and a vector index
- An orchestration script
- A user interface
Weeks of work. Impressive in a demo. Not a system anyone can run.
Agents inherit your enterprise access model
Read and write to systems of record
Owned sources, lineage, freshness, citations
Golden sets, trajectory tests, regression gates
Searchable run history at transaction level
Routing, caching and ceilings per workflow
Policy-as-code, risk tiering, audit trail
Defined checkpoints, escalation and reversal
All eight ship with the IX AI Foundry, so your build starts at the interesting part.
Our Enterprise AI Development Services
Most engagements combine two or more. An agentic workflow almost always needs enterprise knowledge underneath it.
Agentic AI Development Services
Agents that do work rather than answer questions. Multi-step reasoning, tool use, memory, delegation between agents, and human checkpoints wherever authority needs to stay with a person.
Typical Builds- Document intake and validation into a system of record
- Exception triage and resolution workflows
- Decision preparation with human approval retained
- Multi-agent processes spanning several systems
- Task automation with full audit trail
Generative AI Development Services
Applications that read, extract, summarise, draft and generate. Document AI and multimodal processing over the unstructured content where most enterprise work actually lives.
Typical Builds- Unstructured document to structured record
- Contract, claim and application review
- Report, memo and correspondence drafting
- Image, audio and mixed-format processing
- Content generation with policy guardrails
Enterprise Knowledge AI
Retrieval that is grounded, permissioned and citable. Enterprise RAG, agentic RAG, graph RAG, knowledge graphs and enterprise search over your own content, respecting who is allowed to see what.
Typical Builds- Product, spec and compatibility assistants
- Policy, procedure and compliance assistants
- Field service and troubleshooting copilots
- Research and analysis synthesis
- Permission-aware enterprise search
Custom AI Development Services
We provide custom AI solution development for proprietary workflows, predictive applications, and AI embedded in existing products.
Typical Builds- Proprietary process automation
- AI embedded into your own product
- Predictive and forecasting models
- Integration with systems that have no modern API
- Solutions extending an Industry Solution Pack
Decades Of Data & AI Delivery
The scale and experience behind every engagement, from strategy through production.
What "production-ready" actually means here.
These are not optional extras or phase-two items. A build does not ship without them.
Golden sets, trajectory tests and regression gates. We know what accuracy is before release, and we know when it drops.
An agent cannot reach data that a person in the equivalent role could not. Entitlements inherit from your identity provider.
Every run, tool call, retrieved source and decision is recorded and searchable, for debugging and for audit.
Per-workflow budgets, model routing and ceilings. Run cost is designed in rather than discovered in month three.
Human checkpoints, escalation paths and the ability to override or unwind an action that should not have happened.
Public cloud, private cloud, on-premises or hybrid, including private model deployment where data cannot leave.
Architecture, runbooks, evaluation sets and operating guidance. You are not locked in by ignorance.
We measure what the workflow costs before we build, so the improvement is provable afterwards.
From workflow to production in eight to sixteen weeks.
Timelines extend where data needs remediation, where the workflow writes back to a system of record, or where approval cycles are long. We say which applies before we quote.
Discover
Confirm the workflow and the baselineConfirm the workflow, the systems it touches, the data available and the baseline it will be measured against.
Week 1–2Design
Set the boundaries before writing codeAgent design, decision boundaries, human checkpoints, integration approach and the evaluation criteria.
Week 2–4Build
Engineer on the IX AI FoundryEngineered on the IX AI Foundry with your terminology, business rules, thresholds and exception handling.
Week 4–9Integrate
Connect to systems of recordConnect to ERP, CRM, core, dealer, plant and document systems under your permission and security model.
Week 7–12Evaluate
Tune until the threshold is metTest against real cases with your team in the loop. Tune until the accuracy threshold is met, not assumed.
Week 10–14Deploy
Hand over the first measured resultControlled release with human checkpoints, handover to AgentOps and the first measured result against baseline.
Week 13–16Four ways to build with us.
Scoped and time-boxed. You know what you are buying before the first sprint.
Test the hardest assumption against real data and produce evidence a CFO will accept before committing to a full build.
Design, build, integrate, evaluate and deploy a production solution inside your systems, with governance and measurement included.
A standing multidisciplinary team working your AI backlog at your cadence. Architect, engineers, data and evaluation in one unit.
An assessment and remediation plan for an AI build that is not reaching production, whoever started it.
Model independent. Integration obsessed.
We are not a reseller. Components are selected per engagement based on your estate, data residency and workload profile.
- Commercial frontier models
- Open-weight model families
- Enterprise and private models
- Fine-tuned domain models
- Embedding and reranking
- Routing, fallback and caching
- Agent orchestration frameworks
- Multi-agent coordination
- Tool and function calling
- MCP and A2A
- Workflow engines
- Agent memory and registries
- Vector stores
- Knowledge graphs
- Hybrid and graph retrieval
- Document AI and OCR
- Enterprise search
- Permission-aware indexing
- ERP and CRM
- Core banking and origination
- Dealer and service management
- PLM, MES and QMS
- Data warehouses and lakehouses
- APIs, events, EDI and legacy
- Azure, AWS and Google Cloud
- Private cloud and on-premises
- Containers and orchestration
- CI/CD pipelines
- Infrastructure as code
- Hybrid deployment
- Evaluation frameworks
- Tracing and observability
- Regression and golden sets
- Cost and usage telemetry
- Monitoring and alerting
- AgentOps handover
Recognitions and Awards
Our enterprise AI, data, and technology work has been recognized by independent industry organizations and technology communities.
Consulting, development, or managed services?
Most enterprises need two of the three. Here is how to tell which conversation to start.
| AI Consulting | AI Development | AI Managed Services | |
|---|---|---|---|
| The question it answers | What should we build, and is it worth it? | How do we build it so it survives production? | Who keeps it working and improving? |
| Start here if | You have ideas but no agreed priorities or business case | You know the workflow and need it delivered | Something is already live and degrading or unmonitored |
| Typical duration | 4 to 8 weeks | 8 to 16 weeks to first production release | Ongoing |
| Main output | Roadmap, architecture, governance, business case | A working solution integrated with your systems | Uptime, quality, cost control and continuous improvement |
| Learn more | AI Consulting → | You are here | AI Managed Services → |
Why Choose Intellectyx as Your AI Development Partner?
You are not paying us to rebuild orchestration, integration and governance. That is already done.
Discuss Your BuildOrchestration, knowledge services, model gateway, integration fabric, control plane and value measurement come pre-built and hardened.
Reusable vertical IP by business function. Where a pack covers your workflow, configuration replaces a large part of the build.
We built data platforms, warehouses and enterprise applications long before AI. That is the layer where most AI builds actually fail.
The team that designs it knows it will be running it, which changes what gets shipped and what gets logged.
The IX Value Engine baselines the workflow before build and reports the measured change afterwards.
Real Outcomes, Delivered at Scale
See how we help enterprises apply AI to improve operations, decision-making and customer experiences.
Transforming Dealer & Customer Support with AI
An AI-powered knowledge platform streamlined dealer and customer support by delivering faster, context-aware responses and reducing manual effort.
Response
AI Virtual CFO Platform for Smarter Financial Decisions
A multi-tenant AI platform consolidated financial data, automated reporting, and delivered advisor-level insights for thousands of concurrent users.
Reporting
From Customer Requirements to Engineering-Ready Designs
An AI-powered platform converted customer requirements into engineering-ready design inputs, reducing design iterations and accelerating production readiness.
Iterations
Decision Intelligence Agents for Financial Institutions
A unified AI finance engine integrated ERP and credit models to deliver real-time liquidity insights and automated working capital decisions.
Decisioning
Our AI Development Technology Stack
As an enterprise AI development company, Intellectyx works across commercial models, open-weight models, cloud platforms, data systems, orchestration frameworks, and deployment environments.
The IX AI Foundry is our reusable enterprise AI technology foundation. It helps us build, integrate, govern, operate, and measure production AI while working alongside your existing technology investments.
Python
TypeScript
Go
LangChain
AutoGen
CrewAI
LangGraph
GPT-4
Claude
Llama 3
Mistral AI
Pinecone
ChromaDB
FAISS
Weaviate
CrewAI
AutoGPT
BabyAGI
AutoGen AI
AWS Bedrock
Vertex AI
Azure OpenAI
NVIDIA DGX
DeepSpeed
TensorRT
ONNX
Guardrails AI
Moderation API
Voyager
SWARM AI
CAMEL
SK-LLM
OpenCV
YOLO
TF VisionAI Development Solutions Across Key Industries.
Our AI software development services are designed around the workflows, data, systems, risks, and operational requirements of each industry.
Build AI solutions for commercial operations, dealer networks, supply chains, engineering, production, quality, and service.
Explore Manufacturing Financial ServicesDevelop governed AI applications for banking, lending, insurance, wealth management, risk, compliance, and customer operations.
Explore Financial Services Healthcare and Life SciencesCreate secure AI solutions for clinical, research, administrative, enterprise knowledge, and patient support workflows.
Explore Healthcare Retail and E-CommerceBuild AI applications for merchandising, personalization, inventory, pricing, fulfillment, and customer experience.
Explore Retail Consumer GoodsDevelop AI solutions for demand planning, product operations, supply chains, sales execution, and customer engagement.
Explore Consumer Goods Travel, Transportation and LogisticsCreate AI applications for planning, logistics, asset utilization, service delivery, and customer support.
Explore Transportation Energy and UtilitiesBuild governed AI solutions for forecasting, asset management, field operations, compliance, and customer service.
Explore Energy Media and EntertainmentDevelop AI applications for content operations, enterprise knowledge, audience engagement, and workflow automation.
Explore MediaAI Development Questions
Production AI applications and agents integrated with enterprise systems. In our case that means agentic workflows, generative AI applications, enterprise knowledge and retrieval systems, and custom solutions specific to a business. The distinguishing factor is that the output is a system that can be operated, not a prototype.
Typically 8 to 16 weeks to a first production release. Read-only knowledge workflows are fastest. Workflows that write back to a system of record, influence customer decisions or require regulatory approval take longer because integration and control design dominate the effort.
No. Agents read from and write to your existing ERP, CRM, core, dealer, PLM and document systems through the Enterprise Integration Fabric, under the same permission model your people work within.
We are model independent. Commercial, open-weight and enterprise or private models sit behind the IX AI Gateway with routing, fallback, caching and optimization, so model choice is a configuration decision rather than a rebuild.
You do. Customers retain ownership and control of data, enterprise knowledge, permissions, agents, governance policies and deployment choices, along with documentation and runbooks at handover.
Through an evaluation harness built during the engagement: golden sets of real cases with correct answers, trajectory tests for multi-step agents, and regression gates that must pass before any release. Accuracy is measured, not assumed.
Yes. Stalled Build Recovery is a two to four week assessment producing findings and a remediation plan. In most cases the problem is integration, evaluation or governance rather than the model.
Handover to AI Managed Services and AgentOps if you want us running it, or documentation, runbooks and evaluation sets handed to your team if you do not. Agents that are deployed and never evaluated degrade quietly, so somebody has to own it either way.
Yes. Those platforms provide model access and a runtime. We add the domain logic, enterprise integration, evaluation, agent identity and value measurement that turn them into a working enterprise workflow.
Consulting defines what to build, why it matters and what is required for success. Development designs, engineers, integrates, evaluates and deploys the chosen solution. If you already know the workflow and the business case, start here.