— 01 · WEB SERVICES · ELASTICSEARCH DEVELOPMENT

Full Stack ElasticSearch Solutions for Complex Apps

Elasticsearch powers applications that search, analyze, and act on data in milliseconds. We build custom solutions across the Elastic Stack — applications, integrations, migrations, and Kibana dashboards — so you ship semantic search, geolocation features, and intelligent autocomplete without the infrastructure pain.

7,000+
01 / PROJECTS
3,000+
02 / CLIENTS
90+
03 / COUNTRIES
27 yrs
04 / SINCE 1998
— 02 · THE ASK

What we mean by elasticsearch development.

Pair this with our AI & ML practice for the AI-heavy parts and enterprise platform work for deep integrations.

Elasticsearch is the engine for search and analytics. We design full-stack solutions: building applications from the ground up, integrating Elasticsearch into existing systems, migrating from legacy search, and customizing Kibana for ops visibility. Our approach pairs Elasticsearch expertise with multilingual support, geolocation indexing, and dedicated QA at every stage. Whether you're building a mobile app with smart search or migrating an enterprise system to real-time analytics, we architect, code, and ship.

— 03 · WHAT WE SHIP

Inside the build.

  • 01

    Custom Elasticsearch application development

  • 02

    Elasticsearch integration into existing web and mobile applications

  • 03

    Elasticsearch consultation and architecture

  • 04

    Kibana dashboard customization and operational UIs

  • 05

    Elastic Stack migration and replatforming

  • 06

    Cloud integration and DevOps automation

  • 07

    Multilingual search and geolocation indexing

  • 08

    Autocomplete and snippet result features

— 04 · AI WHERE IT EARNS

AI, tuned for
elasticsearch development.

Vertical-tuned models beat generic ones on category-specific signals. The shortlist below shows where AI measurably earns its build cost in this service.

01 · AI

Semantic search that understands intent, not just keywords

02 · AI

Real-time log analysis and anomaly detection for ops

03 · AI

Recommendation engines powered by Elasticsearch ranking

04 · AI

Natural-language indexing for multi-language applications

05 · AI

Intelligent autocomplete with context-aware suggestions

06 · AI

Personalized faceted search for e-commerce and content platforms

07 · AI

Behavioral analytics and user journey analysis

— 05 · BUILT ON

The stack.

ElasticsearchKibanaLogstashBeatsAWS / Azure / GCP (cloud integration)DevOps toolchainsMultilingual analyzersGeospatial mapping libraries
— 06 · THE BENCH

A deep team
ready to ship.

The engineers you'd be working with — architecture, AI, platform, design, and delivery leads, all of them shippers with portfolio work you can verify.

15+ yrs

Lead Architect

System design & scale

10+ yrs

Senior Engineer

Platform engineering

8+ yrs

AI / ML Engineer

Models, pipelines, evals

9+ yrs

Product Designer

UX, research, systems

12+ yrs

Delivery Lead

Roadmap & outcomes

7+ yrs

QA Automation

Quality & reliability

9+ yrs

DevOps Engineer

CI / CD, infra, observability

8+ yrs

Mobile Specialist

iOS + Android shipped at scale

1,200+
Engineers
8 yrs
Avg. Seniority
4
Global Offices
24/7
Delivery Cadence
— 07 · WHY US

Why teams pick us.

01 · BENEFIT

**Real-time insights

** Extract and act on data in milliseconds, not hours, enabling interactive dashboards and live analytics.

02 · BENEFIT

**Semantic understanding

** Search applications that understand intent and context, not just keyword matches.

03 · BENEFIT

**Global reach

** Multilingual indexing and geolocation features work out of the box for international audiences.

04 · BENEFIT

**Scalable architecture

** Handle billions of documents and petabyte-scale data without custom infrastructure engineering.

05 · BENEFIT

**Operational visibility

** Custom Kibana dashboards turn raw logs into actionable intelligence for your ops team.

06 · BENEFIT

**Swift migration

** Move from legacy search systems to Elasticsearch without downtime or data loss.

— 08 · QUESTIONS

Answers for
the evaluation call.

01How is Elasticsearch different from a traditional database?
Elasticsearch is optimized for full-text search and analytics—it indexes and inverts data for near-instant queries on large datasets. Traditional databases excel at transactional consistency; Elasticsearch trades some consistency for speed and scale, making it ideal for search, logging, and analytics workloads.
02Can Elasticsearch handle our multilingual user base?
Yes. Elasticsearch includes analyzers for 30+ languages, so you can index and search Japanese, Arabic, German, Spanish, and English within the same cluster. We configure language-specific tokenization and stemming so your search quality stays high across regions.
03What's the difference between Elasticsearch and Kibana?
Elasticsearch is the search and analytics engine; Kibana is the visualization and ops layer. We often build applications that query Elasticsearch directly via API, while custom Kibana dashboards help your team monitor performance, logs, and alerts.
04How do you migrate existing data to Elasticsearch?
We design a migration pipeline that reindexes your legacy system's data without downtime. Logstash and custom ETL processes move data incrementally, with parallel read/write during the cutover so users see no interruption.
05Does Elasticsearch work with AI and machine learning?
Elasticsearch + machine learning powers semantic search, anomaly detection, and recommendations. We integrate ML pipelines that infer document vectors, rank results by relevance, and surface behavioral patterns your team can act on.
— 10 · SCOPE YOUR ELASTICSEARCH DEVELOPMENT

Ready to ship?

One discovery call, a working POC inside four weeks, and a full build scoped to your metric. That's the engagement path.

hello@indianic.comWhatsApp Chat
RESPONSE TIME
< 4 hours
NDA
On request
FREE POC
3 – 5 days
TRUST
SOC 2 · ISO 27001