APIs that connect your systems and let AI act on them.
Public and internal APIs, integration layers and event pipelines that make your data flow and your agents useful.
What is API development and integration?
API development and integration connects your systems so data flows automatically and, increasingly, so AI agents can act on them. Eazyware designs REST and GraphQL APIs, builds integration layers for CRM, ERP, payments and messaging, wraps legacy systems that have no API, and exposes tools to agents through MCP servers with scoped permissions.
| Service line | Digital Product Engineering |
|---|---|
| Engagement | Scoped build with milestones |
| Duration | Quoted after scoping; typically 8–16 weeks |
| Starting price | $7,000 |
| Typical range | $7,000 – $35,000 |
| Deliverables | 5 listed below |
| Delivered from | Bengaluru, India (IST, UK and US East hours) |
| Code ownership | Client owns code, infrastructure, prompts and documentation |
What problem does it solve?
Systems that don't talk to each other create manual work, stale data and agents with nothing to act on.
How do we approach it?
We design APIs as products: versioned, documented, authenticated, rate-limited and observable, whether they are public or internal. Integration work starts with a map of the systems involved and how data actually flows between them, including the legacy ones with no API, which we wrap with adapters rather than replace. Event pipelines and queues decouple systems so one failure does not cascade. For AI, we expose tools through MCP servers with scoped permissions so agents can act on your systems safely, and every call is logged.
What do clients use it for?
- Public API and developer portal
- CRM, ERP and payment integrations
- Event pipelines between systems
- MCP servers so agents can use internal tools
Is it the right fit?
Good fit when
- Products opening up to partners
- Businesses with systems that do not talk to each other
- Teams preparing for AI agents
Probably not when
- One-off data exports
- Front-end-only work
What do we build?
- REST and GraphQL API design and development
- Public developer APIs with auth, rate limits, versioning, docs
- Integration layers for CRM, ERP, payments, messaging, logistics, banking
- Event-driven pipelines, webhooks, queues
- MCP servers and tool interfaces so AI agents can call your systems safely
- API gateway, monitoring, SLAs
What you get
- APIs
- OpenAPI documentation
- Developer portal (optional)
- Integration connectors
- Monitoring
How does the engagement work?
- 01
Integration map
- 02
API design
- 03
Build
- 04
Test
- 05
Deploy and monitor
What does good look like?
Systems that talk to each other without manual re-keying, an API developers can integrate in an afternoon from the documentation alone, and a monitoring view that shows integration health and failures before customers do. New connectors added in days because the patterns exist. And agents that can use your tools without anyone worrying about what else they might touch.
How does it compare?
| Eazyware | Typical agency | In-house hire | |
|---|---|---|---|
| Time to first result | Sprint Zero in 10 days, then a fixed-scope build | 6–12 weeks of discovery before a proposal | 3–6 months to hire, then ramp |
| Pricing model | Fixed scope, milestone billing, INR or USD | Time and materials, open-ended | Salaries, tooling, management overhead |
| AI depth | Multi-model, evals, cost routing, observability as standard | Often a single vendor API and a prompt | Depends entirely on who you can hire |
| Ownership | Client owns code, infra, prompts and docs | Sometimes retained or licensed back | Owned, but concentrated in one or two people |
| After launch | Care Plans with SLA and AI add-on | Change requests at hourly rates | Ongoing headcount whether or not there is work |
Which pitfalls do we design around?
Integration projects fail on undocumented behaviour in the systems being connected, on tight coupling that turns one outage into many, on no monitoring so failures are silent, and on giving AI agents broad access because scoping seemed like work. We discover behaviour with characterisation tests, decouple with events, monitor everything and scope every tool.
What do we measure?
Every engagement is instrumented. These are the numbers you see in the dashboard and the monthly report, not claims on a website.
- API uptime and p95 latency
- Integration failure rate
- Time to add a new connector
Which technologies do we use?
- Node.js
- OpenAPI
- Redis / BullMQ
- MCP
- API gateway
Who does the work?
A backend engineer with integration experience, an architect for the API design and event model, and, for MCP work, an AI engineer.
What do you need to bring?
Documentation or access for the systems being connected, including credentials for staging environments, a view on data ownership and flow, and, for agent tooling, the list of actions agents should be able to take and who must approve them.
Frequently asked questions
Legacy system with no API?
We wrap it: database adapters, file drops, RPA as a last resort.
MCP?
Yes. We expose your tools to agents with scoped permissions.
Where does this fit?
API Development & Integrations is part of our Digital Product Engineering line. Not sure yet? Start with Sprint Zero, a ten-day discovery whose fee is credited to this build. See all pricing or talk to an engineer.