Generative AI Integration
Plug GenAI into your existing stack securely, observably, and with reversible rollouts. We integrate copilots, RAG, and agents across your apps, data, and workflows.
- / Trust By
Built with LangGraph, ReAct, Python, FastAPI. Tool use, memory/RAG, safety guardrails, and evaluation are built‑in so agents improve over time.
Security & compliance
Observability
Fast rollout
- / Techstack
Built with modern, proven AI technologies
Where we integrate
We connect GenAI to the systems that run your business. (*) Indicates platform support via APIs/partners.
CRM & Helpdesk
HubSpot
Salesforce
Zendesk
Freshdesk
ERP & Operations
Odoo
NetSuite
SAP*
Custom ERPs
Ecommerce
Medusa.js
Shopify*
Custom storefronts
Payment gateways
Data Warehouses
PostgreSQL
BigQuery*
Snowflake*
S3/GCS
Messaging & Events
Webhooks
Queues
Event buses
Streaming
Team Tools
Slack
Telegram
Custom portals
Integration patterns
Choose the right pattern for your latency, reliability, and cost targets. We design for rollback and progressive exposure.
Synchronous APIs
Low-latency REST/GraphQL endpoints for UI calls and server actions.
Asynchronous Queues
Background jobs, retries, and batching for cost-efficient throughput.
Event-Driven
Webhook triggers and event buses to react to business events in real time.
Streaming
Server-sent events and websockets for live updates and partial responses.
Batch & ETL
Daily vectorization, content sync, and index refresh for RAG.
In‑App SDKs
Embeddable widgets and chat UIs for portals, support desks, and CRMs.
What we integrate
High-impact use cases that slot into your current tools and workflows.
CRM Copilots
Draft emails, summarize calls, update fields, and recommend next actions.
Support Automation
Auto-triage tickets, propose answers, escalate with full context + citations.
Ecommerce RAG
AI search, guided discovery, PDP Q&A, and post‑purchase assistance.
Knowledge Ops
Document ingestion, policy assistants, SOP copilots, and compliance checks.
Data & Vector Pipelines
Embed content, schedule refresh, monitor drift, and manage index health.
Cost & Latency Controls
Caching, batching, fallbacks, and tiered models to meet SLAs + budgets.
Reference architecture snapshot
A pragmatic blueprint for adding GenAI to existing systems modular, testable, and reversible.
Layer 1
Layer 2
Layer 3
Layer 4
Layer 5
How we integrate
- / Process
1/6
Systems map, data audit, SLAs, risks, compliance.
Assess
2/6
Pattern selection, API contracts, flags, eval metrics.
Design
3/6
Build adapters, pipelines, and rollout toggles.
Integrate
4/6
Security, cost/latency budgets, monitoring, SLOs.
Harden
5/6
Canary + A/B, playbooks, stakeholder enablement.
Rollout
6/6
Feedback loops, tuning, incident response, reporting.
Operate
- / FAQs
Frequently Asked Questions
- How do you keep latency low?
We design for caching, batching, streaming responses, and tiered model selection keyed to SLAs.
- Can rollouts be reversed?
Yes. Feature flags, canaries, and versioned adapters allow instant rollback without downtime.
- How is data secured?
PII masking, scoped tokens, audit logs, and policy guardrails. We align with your compliance needs.
- Do you work with on‑prem systems?
Yes. We integrate via secure gateways, queues, or scheduled sync with strict network policies.
Ready to integrate GenAI into
your stack?
Let’s pick the right pattern, wire it safely, and roll out with measurable impact.