How we help
Three engagements.
Choose the problem you need to solve.
01
Agent Harness Build & Audit
Your agent loops or calls the wrong tool. We trace the failure and fix context, tool use and recovery.
Discuss this workScope and deliverables
The work
- Tool contracts and context management
- State, checkpoints and recovery paths
- Trace instrumentation and replay
- Task evaluation, cost and latency profiling
What you receive
- An audited or implemented agent harness
- A failure map with reproducible traces
- Task tests and regression checks
- A runbook and engineering handover
02
LLM Performance Diagnostic & Evals
You cannot tell whether the model is getting better. We build task-specific evals and identify what is holding it back.
Discuss this workScope and deliverables
The work
- Task definition and representative evaluation sets
- Model, prompt and retrieval baselines
- Failure taxonomy and data-quality review
- Scoring calibration and human review
What you receive
- A runnable evaluation harness
- A baseline report with failure breakdowns
- A prioritised improvement plan
- Regression gates for future experiments
03
Domain Model Improvement Sprint
Sprint or ongoing Model Improvement Partner.
Your model falls short on domain tasks. We curate data, run post-training experiments and measure the change.
Discuss this workScope and deliverables
The work
- Data curation, synthetic generation and quality checks
- SFT, LoRA and post-training experiments
- Multi-node FSDP / DeepSpeed training, checkpointing and experiment tracking
- Held-out evaluation, regression and cost comparisons
What you receive
- A versioned dataset and data-quality checks
- A reproducible training pipeline
- Candidate checkpoints and comparison reports
- A documented next-iteration plan
What is your model getting wrong?
Send Avinash a failing example and what you have tried.