AI Coworkers
01Custom Claude-powered agents that operate your systems natively — reading, writing, acting through your APIs. Roles like Accountant, HR, Sales Ops, Compliance, Support.
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- Custom Software DevelopmentWeb apps, SaaS, integrations
- Custom E-Commerce Web DevelopmentStorefronts, checkout, payments, marketplaces
- Mobile App DevelopmentiOS + Android + cross-platform
- Application DevelopmentEnd-user products from MVP to scale
- Web Design & DevelopmentMarketing sites + e-commerce + portals
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- How we workOur philosophy and project management process
AI & Business Process Automation
AI that operates your business, not just answers questions.
Native AI agents on Claude Opus + native workflow automation — the same architecture that powers the EXO NODES AI Workforce. Sales follow-up, invoice extraction, WhatsApp support, document review, compliance monitoring. Real work, audited, approvable.
Since 20171,200+ projects deliveredNative AI Workforce architecture · Not a Zapier or Make wrapper
Capabilities
What we build.
Every engagement is scoped to your specific stack and roadmap — no cookie-cutter templates, no generic listicles.
WhatsApp + email support agents
02Multi-channel first-line support with intelligent hand-off to humans. Trained on your knowledge base, anti-spam scoring, per-tenant rate limits.
Document extraction
03Bills, receipts, contracts, KYC documents parsed into structured data. Multi-language including Arabic. Confidence scoring + approval queue for review.
Workflow automation
04Trigger → condition → action pipelines that survive real-world edge cases. BullMQ-backed, idempotent, retriable, with per-tenant audit trails.
Knowledge search
05RAG-style retrieval over your Confluence, Notion, Google Drive, SharePoint. Answers cite the source; never hallucinates policy that isn't in the corpus.
Custom AI features
06Menu generators, product-description writers, translation pipelines, categorisation, sentiment analysis — whatever the product needs, wired to your data model.
Governance + approvals
07Every AI action logged. High-value actions gated by an approval queue with per-role permissions. Kill switch on the model, budget cap per tenant.
Proof-of-concept in weeks
08Two-week paid PoC on one workflow — you see it working on real data before committing to a full rollout. No open-ended "AI transformation" retainers.
Our process
How we run every projectStart to finish, step by step.
7 steps from the first conversation to life after launch. Durations are typical; your plan sets the real ones.
Step 1: Identify
Workshop to find 2-3 workflows where AI moves a needle, usually where people re-type data or answer the same question 100+ times a day.
- You get: Shortlist of workflows
- Typical duration: About 1 week
Step 2: Data & risk review
We check the data each workflow needs, where it lives, who may see it and which decisions must stay with a person.
- You get: Data and risk notes
- Typical duration: Under 1 week
Step 3: Prototype
Two-week proof of concept on one workflow using real data. You approve accuracy and latency numbers before we scope the rollout.
- You get: Measured proof of concept
- Typical duration: 2 weeks
Step 4: Build + govern
Production build with audit trail, approval queue, budget cap and kill switch from day one. Compliance-ready, not a demo.
- You get: Production workflow
- Typical duration: 4–10 weeks
Step 5: Pilot
A controlled rollout to a small group, with outputs checked by people before they count.
- You get: Pilot results
- Typical duration: 2–4 weeks
Step 6: Roll out & train
Wider rollout, training for the team that works alongside it, and clear rules for when a case goes to a person.
- You get: Trained team and escalation rules
- Typical duration: 1–2 weeks
Step 7: Operate
Monthly accuracy review, prompt tuning and cost analysis. We tell you honestly when a workflow doesn't justify the AI cost and should be re-hand-coded.
- You get: Monthly accuracy and cost review
- Typical duration: Ongoing
Common questions
01Is this different from Zapier or Make?
Yes — categorically. Zapier/Make chain SaaS APIs together with pre-canned triggers and simple conditional logic. Our AI agents reason, plan, and act — they can read a customer email, extract intent, look up context in your database, draft a reply, escalate to a human if unsure, and log the whole trace. When rules-based automation is the right answer, we still recommend Zapier/Make. When it isn't, we build a real agent.
02Which AI model do you use?
Claude Opus 4.7/4.8 by default (Anthropic), with a model router (`AgentModelRouter`) that can fall back to OpenAI GPT-4/5 or Gemini for specific tasks. We build against a capability, not a vendor — you're never locked to one provider.
03How do you handle hallucinations?
Three defenses: (1) retrieval-augmented generation — the model cites source documents, not memorised training data; (2) validated tool calls — the model calls your APIs, and the API validates inputs; (3) approval queues on high-stakes actions (invoicing, payments, sending customer messages). "No hallucinations" is a marketing claim; auditability is a product decision — we ship the second.
04Do our documents leave the UAE for AI processing?
By default yes — Anthropic's Claude API runs from US datacenters. For UAE-resident-only workloads we deploy Claude via AWS Bedrock in Middle East (me-central-1) — the requests never leave region. Regional hosting has higher provider usage rates, which we set out in the proposal; the residency guarantee is provider-level.
05Can the AI access our accounting system?
Yes — through our OS06 connector layer. Native support for Zoho Books, QuickBooks, Xero, Tally, SAP B1, NetSuite, and Odoo. The AI reads (invoices, customer master, GL) and writes (drafts to review) with full audit trail per action.
06What if the AI makes a mistake?
Every action writes to an audit chain (`RegulatedEventLog`). Approval-gated actions (payments, invoicing, customer messages) require a human "Approve" before firing. Non-approval-gated actions are reversible or clearly logged. We build for "trust but verify," never "set and forget."
07How do I know it's working?
We instrument every workflow with success metrics (accuracy, cycle-time reduction, cost saved) and review monthly. If the numbers don't justify the cost, we recommend switching that workflow back to rules-based automation — we'd rather lose the retainer than sell you a demo.
Free call · 30 minutes
Free 30-minute scoping call
Talk a software idea through with an engineer before you spend anything.
- 30-minute call
- No obligation
- Arabic or English
Ready to start?
15-minute scoping call, written proposal within one business day. No pushy sales.
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