AI Development Services That Grow Revenue and Cut Costs
AI Development ThatGrows Your RevenueCuts Costs at ScaleWins More CustomersShips in WeeksGrows Your Revenue
Senior AI engineers who turn your data into products that win customers and cut costs. Fixed quotes, measured results and code in your repositories from day one.
Most AI budgets are lost in the same few places. We design each engagement around them from the first call.
01 / 04
Pilots that never reach production
Most AI work stalls between a promising demo and a system people rely on. The demo was never measured, never integrated and never owned.
How we fix it
Every engagement starts with a baseline metric and a test set built from real cases, and the production plan is part of the first quote.
02 / 04
Data that is not ready for AI
Records are scattered across a CRM, a helpdesk, spreadsheets and PDFs, so the model has nothing clean or current to work from.
How we fix it
A data readiness audit in week one tells you what is usable now, and we build the pipelines before we tune a single prompt.
03 / 04
Costs nobody can predict
Open-ended estimates, surprise model bills and infrastructure sized for a demo make it hard for finance to say yes twice.
How we fix it
Fixed quotes per phase, model costs estimated per request before you commit, and a cost dashboard live from the first release.
04 / 04
No in-house AI team to run it
Hiring senior AI engineers takes months, and a system nobody on your side understands becomes a liability after launch.
How we fix it
A senior team ships it with you, then hands over runbooks, eval suites and pairing sessions so your engineers can extend it.
[ Partner programs ]
BuiltWiththePlatformsThatLeadAI
Our AI engineering is recognized by the programs that build the models and the infrastructure, so your project starts on proven ground.
OpenAI Select Partner
Part of OpenAI's partner network. We build production assistants, agents and document pipelines on GPT models.
Claude Select Partner
Select Services Partner in Anthropic's Claude Partner Network. We build agents, assistants and coding workflows on Claude models and Claude Code.
AWS for Startups
Backed by AWS for Startups. AI workloads deployed on AWS with Bedrock, SageMaker and serverless infrastructure.
NVIDIA Inception
Member of NVIDIA Inception, the program for AI startups. GPU-accelerated training and inference where a workload needs it.
[ Capabilities ]
TheFullAIBuild,UnderOneRoof
Shipping AI takes more than a model call. We cover each discipline a production system needs, and we package proven patterns so you do not pay to reinvent them.
A ranked portfolio of opportunities with baselines, data checks and a business case for each, so budget goes to work that can be measured.
02
Data engineering
Pipelines, cleaning, labeling and feature stores that give models fresh, trustworthy inputs from your CRM, ERP, warehouse and documents.
03
Model selection and tuning
Benchmarks of hosted and open-weight models on your own test set, followed by prompt design, retrieval or fine-tuning where it pays off.
04
Agents and automation
Tool-using agents and AI workflows that act in your systems with approvals, limits and logs, from a single task to cross-team processes.
05
AI applications
Web, mobile and internal apps built around the model, with the UX details that make AI output easy to trust, edit and act on.
06
Packaged AI solutions
Reusable starting points for chatbots, document extraction, semantic search and agent integrations, adapted to your data instead of built from zero.
07
MLOps and LLMOps
Versioned prompts and models, CI evals, drift monitoring, cost dashboards and rollback, so the system keeps working after launch day.
08
Security and governance
Access controls, PII handling, audit logs and model risk documentation aligned to your compliance needs.
[ Use cases ]
AIAcrossEveryDepartment
Most companies find their first wins in the teams with the most repetitive, data-rich work. These are the areas where we usually start.
01Customer support
01
Customer support
Assistants that answer from your help center, triage and tag incoming tickets, draft replies for agents and summarize long threads before handoff.
Shorter queues and more consistent answers
02Sales and revenue
02
Sales and revenue
Lead enrichment, intent scoring, call summaries pushed to the CRM and forecast notes that explain which deals moved and why.
Reps spend more hours with buyers
03Operations
03
Operations
Document intake, order exceptions, scheduling and quality checks handled by models that read forms, emails and PDFs and post clean data to your systems.
Less manual re-keying between tools
04Finance
04
Finance
Invoice and receipt extraction, spend categorization, anomaly flags on payments and month-end variance commentary drafted for review.
Faster close with a clear review trail
05Product and engineering
05
Product and engineering
AI features inside your own product: smart search, recommendations, in-app copilots and feedback analysis that clusters thousands of user comments into themes.
Features customers notice and pay for
06Systems that learn from feedback
06
Systems that learn from feedback
Adaptive models that capture approvals, corrections and outcomes, then retrain or re-rank on a schedule so accuracy improves as usage grows.
Quality that rises with every month of use
01
Customer support
Assistants that answer from your help center, triage and tag incoming tickets, draft replies for agents and summarize long threads before handoff.
Shorter queues and more consistent answers
02
Sales and revenue
Lead enrichment, intent scoring, call summaries pushed to the CRM and forecast notes that explain which deals moved and why.
Reps spend more hours with buyers
03
Operations
Document intake, order exceptions, scheduling and quality checks handled by models that read forms, emails and PDFs and post clean data to your systems.
Less manual re-keying between tools
04
Finance
Invoice and receipt extraction, spend categorization, anomaly flags on payments and month-end variance commentary drafted for review.
Faster close with a clear review trail
05
Product and engineering
AI features inside your own product: smart search, recommendations, in-app copilots and feedback analysis that clusters thousands of user comments into themes.
Features customers notice and pay for
06
Systems that learn from feedback
Adaptive models that capture approvals, corrections and outcomes, then retrain or re-rank on a schedule so accuracy improves as usage grows.
"SajalTech gave us the digital platform our service always deserved. Clients can now find us, understand our value immediately, and submit their documents effortlessly. It's the best business decision we've made."
CCEOLetterCrafts, Singapore
"Knowledgeable, efficient, and ahead of schedule. Will hire again."
TMTom McGrathFounder, Tipperary | eIrish.com
"I had the pleasure of working with Sajal Tech on a travel website, and it was an incredible experience from start to finish. They demonstrated professionalism, clear understanding of requirements, and excellent communication throughout."
DKDaniel KwekaCEO, Darius Digital
"SajalTech didn't just build us a marketplace: they built us the best domain trading platform we've seen. The automated tools and analytics transformed how our sellers operate, and buyers trust the experience completely."
CCEODomainMarkt
"SajalTech gave us the digital platform our service always deserved. Clients can now find us, understand our value immediately, and submit their documents effortlessly. It's the best business decision we've made."
CCEOLetterCrafts, Singapore
"Knowledgeable, efficient, and ahead of schedule. Will hire again."
TMTom McGrathFounder, Tipperary | eIrish.com
"They completed our project even when the scope changed slightly. They were cooperative when we wanted to add or modify features."
AUArda UygurFounder, Hallolur
"The SajalTech team delivered exactly what we needed: a modern website and ERP system that transformed how our institution operates. Information is accessible, processes are automated, and our staff can focus on education, not paperwork."
PPrincipalGovernment Law College Ernakulam
"SajalTech gave us something that simply didn't exist before: a platform that puts retail traders on equal footing with professionals. The real-time data and clean UX have made it the best tool in our users' arsenal."
FFounderPower of Volatility
"They completed our project even when the scope changed slightly. They were cooperative when we wanted to add or modify features."
AUArda UygurFounder, Hallolur
"The SajalTech team delivered exactly what we needed: a modern website and ERP system that transformed how our institution operates. Information is accessible, processes are automated, and our staff can focus on education, not paperwork."
PPrincipalGovernment Law College Ernakulam
[ How we deliver ]
HowanAIProgramRunsWithUs
We prove value on one use case first, then turn what worked into a repeatable platform for the next ones.
1 to 2 weeks
Discovery and roadmap
Workshops with department leads, a data readiness audit, baseline metrics and a ranked list of use cases with costs and expected returns.
AI roadmap
Data audit
Fixed quote for pilot
3 to 6 weeks
Pilot build
The top use case built on real data, scored against its baseline and shown to users in weekly demos.
Working pilot
Eval report
3 to 8 weeks
Production rollout
Integrations, security review, monitoring and training for the teams who will use it, followed by a staged launch.
Live system
Runbooks
Team training
Ongoing
Platform and expansion
Shared data, retrieval and eval components reused for the next use cases, with feedback loops and monthly cost and quality reviews.
Shared AI platform
Quarterly roadmap
[ Architecture and tooling ]
TheAIStackWeBuildandOwnWithYou
Every AI product we deliver follows the same layered shape. Each layer can be upgraded on its own as models and needs change.
The surfaces where people use AI and give feedback.
Web and mobile apps
In-product copilots
Chat and messaging
Internal dashboards
Models, Frameworks and Platforms
We stay vendor-neutral and choose per workload. A typical product mixes a frontier model, a cheaper fast model and some classic ML.
Frontier models
OpenAI GPT · Claude · Gemini · Grok · Qwen Omni
Open-weight and on-device
Llama · Mistral · DeepSeek · Liquid AI · LM Studio
Agents and orchestration
LangGraph · CrewAI · Google Genkit · Vercel Eve · MCP · A2A protocol
Start with a workflow that has high volume, clear inputs and a metric you already track, such as handle time or error rate. We run a short discovery to rank candidates by value and data readiness, then pilot the top one. Starting narrow makes the result easy to measure.
How much does AI development cost?
Packaged solutions like a support chatbot start from $1,500, a measured pilot on one use case from about $8,000, and multi-use-case products or platforms from $30,000. Model usage is billed by the provider and we estimate it per request before you commit.
How long until we see results?
Discovery takes 1 to 2 weeks and a pilot on real data takes 3 to 6 weeks, so a pilot engagement runs 4 to 8 weeks in total. Most clients have measured results from the pilot within two months of the first call.
Do we need a lot of data to get started?
Not usually. Modern language models work well with retrieval over your existing documents and records, and classic ML needs more history only for prediction tasks. Our data audit tells you what is usable now and what to clean up.
What is adaptive AI and do we need it?
Adaptive AI learns from feedback after launch: reviewer corrections, accepted suggestions and real outcomes are captured and used to retrain or re-rank the model. It is worth adding once a system has steady usage, because accuracy then improves with volume instead of staying flat.
Should we build custom AI or buy an off-the-shelf tool?
Buy when a SaaS tool covers the workflow and your data can live there. Build when the workflow is core to your business, needs your proprietary data, or must integrate deeply with your systems. We often combine both and say so in the roadmap.
Which models and clouds do you work with?
We work with OpenAI, Anthropic, Google, xAI and open-weight models such as Llama and Mistral, hosted on AWS, Azure or Google Cloud. Choices are made by benchmarking on your test set, not by vendor preference.
How do you keep our data safe?
Data stays in your cloud or a region you pick, model endpoints use zero-retention settings, and access is role-based and logged. We are ISO 27001 certified and sign an NDA on request.
Who owns the models, prompts and code?
You do. All code, prompts, fine-tuned weights, eval sets and documentation transfer to you, and we include 30 days of post-launch support with optional monthly maintenance after that.
Can you work with our in-house team?
Yes. Many clients pair our senior AI engineers with their own developers, and we hand over runbooks and pairing sessions so your team can run and extend the system.
