Agent design and roles
Define what an agent may do, what it must escalate, and how humans approve high-impact actions—before wiring tools or models.
AI and ML
from pilots to production
Models, retrieval, and agent-style workflows when the business case is clear—AWS-first (Bedrock, SageMaker) with evaluation, cost, and guardrails your risk owners can stand behind.
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Client Projects Delivered
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Engagement Models
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Client Retention
What we deliver in AI and ML
End-to-end work when the problem is well framed—otherwise we help you narrow scope before you over-invest.
Agent creation
Build AI agents that fit your workflows
We design and implement agent-style systems: language models plus tools, retrieval, and policies—not generic chat wrappers. Scope stays tied to measurable outcomes, safety boundaries, and how your team will run them in production.
Tools, APIs, and orchestration
Safe calls to your systems: auth, idempotency, timeouts, and structured outputs so agents fail closed instead of looping blindly.
RAG and knowledge boundaries
Retrieval tuned to freshness, access control, and citation-style answers where stakeholders need audit trails—not a dump of embeddings.
Evaluation and production on AWS
Test sets, regression checks, logging, and cost guardrails. We often ship on Bedrock and SageMaker patterns your cloud team can operate.
AI work tied to real outcomes
Interfaces and systems where models support decisions your team can defend—not demos disconnected from operations.
Retail AI Platform
An AI-driven analytics platform that helps retailers predict demand, personalize offers, and boost customer engagement. It delivers data-driven insights for smarter decision-making and increased revenue.
Stack and platforms
Tools we use for serious ML work
Frameworks and cloud services chosen for your constraints—not every logo at once.
Model Frameworks
Libraries we use when they match your problem—not by default.
Data Science
Exploration and training code your team can reproduce and extend.
Processing
Batch and stream patterns sized to your data and budget.
MLOps & Tools
Packaging, notebooks, and git workflows that survive handover.
Infrastructure
AWS-first with Azure or GCP when your estate requires it.
What Our
Clients Say.
Teams in fintech, education, health, and logistics partner with us for AWS-grounded delivery and long-term product support.
"Ghawk stepped in during a critical situation and was available almost immediately. Clear communication, fast execution, and strong ownership throughout. I would gladly work with them again."
S
SantoshProduct Lead // Mid-market SaaS
"The Ghawk team worked closely to the requirements and delivered exactly what we needed. The output matched expectations and the handover was smooth."
VB
Vamsi BhumireddyEngineering // Client Team
"Responsive and delivered the requested audit document clearly. We also had a constructive discussion around repository ownership, deployment transparency, and production readiness, which made the engagement more valuable overall."
Y
YaelFounder // Startup
"Shweta delivered all assigned tasks and demonstrated strong technical understanding. Reliable execution and good communication. I would rehire again."
SN
Sandeep NarayanProject Manager // Client Team
"Really glad to have their help. Quick learner, great communicator, and patient under stress. They kept things moving when timelines were tight."
EK
Elliot KellyFounder // SaaS
"Excellent communication and a knowledgeable technician. Strong follow-through and clean delivery. I would definitely hire again."
RG
Russ GuillemotEngineering Manager // Client Team
"Top-notch experience. Professional, proactive, and deeply knowledgeable from day one. Communication was crisp, deadlines were met, and expectations were consistently exceeded."
BS
Bobby ShreckengostFounder // Product Company
"Working with Shweta was a great experience. She is an experienced Node.js developer and delivered reliably against the requirements."
SJ
Sid JClient // Node.js Project
"Ghawk Technologies were wonderful to work with. Communication was consistent and proactive, and they met our expectations for the project."
JC
Jonathan CroyClient // Product Team
"Great experience working with the Ghawk team. Responsive, collaborative, and easy to work with throughout the engagement."
AP
Abhishek PanwarClient // Partner Team
"Great work by the Ghawk team again. Strong delivery and dependable communication as always."
JC
Jonathan CroyClient // Product Team
"Ghawk stepped in during a critical situation and was available almost immediately. Clear communication, fast execution, and strong ownership throughout. I would gladly work with them again."
S
SantoshProduct Lead // Mid-market SaaS
"The Ghawk team worked closely to the requirements and delivered exactly what we needed. The output matched expectations and the handover was smooth."
VB
Vamsi BhumireddyEngineering // Client Team
"Responsive and delivered the requested audit document clearly. We also had a constructive discussion around repository ownership, deployment transparency, and production readiness, which made the engagement more valuable overall."
Y
YaelFounder // Startup
"Shweta delivered all assigned tasks and demonstrated strong technical understanding. Reliable execution and good communication. I would rehire again."
SN
Sandeep NarayanProject Manager // Client Team
"Really glad to have their help. Quick learner, great communicator, and patient under stress. They kept things moving when timelines were tight."
EK
Elliot KellyFounder // SaaS
"Excellent communication and a knowledgeable technician. Strong follow-through and clean delivery. I would definitely hire again."
RG
Russ GuillemotEngineering Manager // Client Team
"Top-notch experience. Professional, proactive, and deeply knowledgeable from day one. Communication was crisp, deadlines were met, and expectations were consistently exceeded."
BS
Bobby ShreckengostFounder // Product Company
"Working with Shweta was a great experience. She is an experienced Node.js developer and delivered reliably against the requirements."
SJ
Sid JClient // Node.js Project
"Ghawk Technologies were wonderful to work with. Communication was consistent and proactive, and they met our expectations for the project."
JC
Jonathan CroyClient // Product Team
"Great experience working with the Ghawk team. Responsive, collaborative, and easy to work with throughout the engagement."
AP
Abhishek PanwarClient // Partner Team
"Great work by the Ghawk team again. Strong delivery and dependable communication as always."
JC
Jonathan CroyClient // Product Team
ML delivery
From data to dependable models
Deep learning, classical ML, and ops in one thread—scoped so each phase has an exit criterion your stakeholders understand.
Model development and benchmarking
Transformers, classical ML, or hybrid stacks—trained and compared against baselines with latency and cost budgets your product can afford.
Data and feature readiness
Cleaning, labeling strategy, leakage checks, and feature stores or pipelines that stay in sync with how data arrives in production.
Deployment and serving
Batch and online inference, autoscaling, and rollback-friendly releases on Kubernetes or managed endpoints—aligned to your SRE model.
Monitoring and retraining
Quality and drift signals, retrain triggers, and governance hooks so models age predictably instead of silently degrading.
Discovery and success metrics
Problem framing, ethical constraints, and measurable outcomes agreed before heavy spend on data or compute.
Why teams work with us
Grounded ML and agents—not slide-deck AI.
Measure before you scale
Baselines, eval sets, and cost envelopes agreed with stakeholders—not vanity metrics after the fact.
Production-minded ML
We ship versioned models, evaluation harnesses, and deployment paths your team can run—not notebook-only experiments with unclear ownership.
MLOps that match your cadence
CI for training artifacts, promotion gates, drift signals, and retraining when data or quality thresholds justify it—not automation for its own sake.
Data and features you can trust
Pipelines, contracts, and access patterns aligned to how your warehouse and applications actually behave so models do not learn on fiction.
Common questions
AI and agent FAQs: scope, AWS fit, safety, data ownership, and how pilots turn into production.
A model project optimizes predictions or generations against data you control. An agent adds orchestration: tools, policies, memory, and human checkpoints. We scope which pattern fits your risk and ROI before building.
Grounding, retrieval, structured outputs, allow-lists for tools, rate limits, and evaluation sets tied to your domain. High-stakes paths get explicit human approval or hard stops—not prompt hope.
Usually a narrow pilot: one workflow, clear metrics, offline and online evaluation, and a production path sketched before scaling spend. We avoid open-ended research without exit criteria.
We are AWS-first (Bedrock, SageMaker, Lambda, observability stacks) and integrate with your existing IdP and data boundaries. Other clouds are possible when your constraints require it—we call that out early.
Ownership and retention follow your contract or SOW. We document what lives in your accounts versus ours during build, and what must be purged after handover.
A model project optimizes predictions or generations against data you control. An agent adds orchestration: tools, policies, memory, and human checkpoints. We scope which pattern fits your risk and ROI before building.
We are AWS-first (Bedrock, SageMaker, Lambda, observability stacks) and integrate with your existing IdP and data boundaries. Other clouds are possible when your constraints require it—we call that out early.
Grounding, retrieval, structured outputs, allow-lists for tools, rate limits, and evaluation sets tied to your domain. High-stakes paths get explicit human approval or hard stops—not prompt hope.
Ownership and retention follow your contract or SOW. We document what lives in your accounts versus ours during build, and what must be purged after handover.
Usually a narrow pilot: one workflow, clear metrics, offline and online evaluation, and a production path sketched before scaling spend. We avoid open-ended research without exit criteria.
Plan your next AI or agent initiative with us
Models, RAG, and production workflows
Share the workflow, data constraints, and success metrics. We respond with a realistic approach—stack, evaluation plan, and how we would collaborate with your team.
OUR PRESENCE
D270 Phase 8B, Industrial Area, Sector 74, Mohali, Punjab, India 160059
Your ideas are safe to share here
We treat what you send as confidential. For datasets, roadmaps, or commercial detail, we can sign a mutual NDA before or right after our first substantive call—mention it in your message or when we reply.