AI stack · Agentic memory
A vector store is not memory.
Your agent needs a profile, working context, and a record of what was decided. We pick graph, session or identity memory from the job, and keep permissions attached. The first week is in the org, reading what already exists.
Certified Partner since 2010 · MVP Hall of Fame · 200+ agents in production · UAE and US desks
- 01Models · Claude, Gemini, OpenAI, Bedrock
- 02Agents · Agentforce, CrewAI, ADK, A2A
- 03Memory · Neo4j, Cognee, RAG
- 04Identity · IndyKite, SSO, entitlements
- 05Governance · policy, audit, human override
On this layer
What we put in.
The honest no: if the work is a software factory with a named delivery date, we are the wrong partner.
Where it shows up
The work this layer does.
Use cases where these tools carry the job. Each one names the stack.
Legal document review
Clauses, parties, and obligations as a graph, not a folder.
Contract management
Which clause affects which vendor, in one traversal.
Data analytics
Join paths the warehouse never modelled cleanly.
Cultural heritage guide
Works, places, and people linked the way curators think.
AI Customer Service Transformation
The agent remembers the last three cases, not just this call.
Golden Visa screening
Document and eligibility memory across a long application.
Recruitment screening
Candidate context that survives more than one recruiter.
Health awareness
Coaching that remembers the last pledge, in the right language.
Compliance monitoring
Every agent action tied to an identity, not a shared key.
Questions
What buyers ask us.
- Why not just use a vector database?
- Similarity search finds text that looks alike. It does not know who the customer is, what was agreed last week, or who may see a record. Graph and identity layers carry those facts.
- Does memory work with Salesforce Data Cloud?
- Yes. Data Cloud can hold the unified profile and vectors as context. We add graph or session memory where the agent needs relationships or history that Data Cloud does not model.
- Who can see what the agent remembers?
- The same people who could see the source records. Memory entries inherit permissions, and we keep an audit trail of what was stored and when it was used.
The rest of the stack
One layer is not a system.
The plane this layer lives in, and the other four layers.
Memory plane
Profile, context, and what was decided.
Models
The reasoning layer. We pick the model that fits the job, then deploy it so data stays where it should.
Agentic systems
How agents plan, call tools, and talk to each other. Frameworks and protocols, not a single vendor lock-in.
Automation and voice
Workflows and voice agents that connect models to Salesforce and the rest of the stack.
How we engage
Deployment and governance. The work that turns a pilot into a production system.
Before you pick a partner
Read these first. Then call anyone.
Our buyer guides. They apply whether or not you hire us.
Choosing an AI partner in the UAE
Five kinds of partner compared, the PDPL, DIFC, Arabic and WhatsApp questions, and red flags.
Choosing an AI implementation partner
Evaluation criteria, deployment models, governance fluency, and red flags.
AI partner evaluation framework
A five-part scorecard: depth, governance, integration, security, delivery.
Questions to ask an AI partner
Architecture, security, governance, pricing, and who is accountable.
AI partner vs in-house team
Hiring timelines, real costs, and dependency risk, scenario by scenario.
AI pilot to production
Which of the four ways your pilot stalled, and the sequence that moves it.
The brief
Send the situation.
Name the process. We tell you which layer is missing.