We design, build, and deploy agentic AI systems that automate complex business workflows end-to-end, combining LLMs, decision logic, and enterprise data into intelligent autonomous agents.
Why Choose Us
From proof-of-concept to production, we've deployed AI solutions across media, healthcare, retail, financial services, and automotive.
We build on Salesforce Agentforce, custom LLM stacks, and hybrid architectures — choosing the right tool for your specific use case.
Every agent we build includes guardrails, escalation paths, and oversight mechanisms — because enterprise AI must be trustworthy.
20+ years of data engineering means your agents are grounded in clean, governed, high-quality data — not garbage in, garbage out.
AI Products
Live products from Decision Foundry that show what agentic AI looks like in production — each one solves a specific marketing-data problem at enterprise scale.
What We Deliver
Evaluate your data maturity, infrastructure, and use cases to build a prioritised 90-day AI roadmap.
Build autonomous agents for document processing, lead qualification, customer support, research synthesis, and more.
Design systems where multiple specialised agents collaborate — with supervisor patterns, handoff logic, and shared memory.
Ground your agents in your proprietary data using retrieval-augmented generation, custom fine-tuning, and vector search.
Connect AI agents to your existing business systems — CRM, ERP, marketing automation — to execute real actions, not just generate text.
Agent tracing, cost monitoring, drift detection, compliance controls, and performance dashboards.
Featured Article
See how agentic AI moves CRM beyond insight to execution — automating decisions, workflows, and customer engagement at enterprise scale.
Why It Matters
Deploy AI that integrates with your existing architecture — not a science project that lives in a notebook. Production-grade, scalable, and maintainable.
Automate the 80% of workflows that are repetitive and rule-based, freeing your team to focus on the 20% that requires human judgment and creativity.
AI agents that qualify leads, personalise outreach, optimise campaigns, and accelerate deal cycles — driving measurable revenue impact.
Common Questions
Agentic AI describes AI systems that move beyond answering questions to taking actions. Instead of static prediction models or one-shot generative responses, agents plan multi-step workflows, query systems, make decisions, and execute work — with or without human approval at each step. The shift is from "AI that recommends" to "AI that acts." Examples: an agent that triages support tickets and resolves Tier-1 issues, or one that monitors campaigns and reallocates budget.
Four workstreams: custom AI agent design and deployment, AI-native application development, AI-powered workflow automation, and agent-driven marketing intelligence. We work across Salesforce Agentforce, Azure AI Foundry, Anthropic Claude, OpenAI, and open-source agent frameworks — choosing the stack that fits your data and governance constraints.
Generative AI produces content (text, code, images) when prompted. RPA automates rigid screen-scraping workflows — fast but brittle. Agentic AI sits in the middle: it reasons over context, makes decisions, calls tools, and recovers when things go wrong. Think of generative AI as a writer, RPA as a worker following a script, and agentic AI as a junior analyst who can plan, ask clarifying questions, and adjust mid-task.
A proof-of-value with one focused agent typically runs 6–10 weeks. Production-grade single-agent deployments run 3–4 months including governance, monitoring, and rollback design. Multi-agent programs and AI-native applications run 4–8 months. Cost varies widely — a Service Agent on existing Salesforce data starts around $80K, while a custom AI application with novel data integrations can run $250K+. Every engagement starts with a free discovery call and readiness assessment.
Most failed AI projects had two problems: (1) the underlying data wasn't clean enough for the model to be reliable, and (2) the AI wasn't connected to systems where it could actually act. Agentic AI fixes #2 — agents call APIs, update records, and execute workflows. We fix #1 by always starting with a data audit. We'll tell you honestly if your environment is agent-ready before you commit.
We're one of the rare consultancies certified across both Salesforce AI (Agentforce, Einstein, Data Cloud) and the broader enterprise AI stack (Databricks Premier, Snowflake Cortex, Azure AI). Since 2004 we've embedded engineers inside enterprises — so our agents are designed by people who understand the workflows they're automating, not by a team that's never set foot in your operations. SOC 2 compliant, GDPR capable, and zero AI vapor-ware in our delivery history.